The Terms of Trade and the Rise of Argentina in the Long …etheses.lse.ac.uk/918/1/Francis_Terms-of-trade-rise-of-Argentina-19t… · The Terms of Trade and the Rise of Argentina

The Terms of Trade and the Rise of Argentinain the Long Nineteenth Century

Joseph A. Francis

A thesis submitted to the Department of Economic History of the London School of

Economics and Political Science for the degree of Doctor of Philosophy.

December 2013.

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Declaration

I certify that the thesis I have presented for examination for the MPhil/PhD degree of

the London School of Economics and Political Science is solely my own work other

than where I have clearly indicated that it is the work of others (in which case the

extent of any work carried out jointly by me and any other person is clearly identified

in it).

The copyright of this thesis rests with the author. Quotation from it is permit-

ted, provided that full acknowledgement is made. This thesis may not be reproduced

without my prior written consent.

I warrant that this authorisation does not, to the best of my belief, infringe the

rights of any third party.

I declare that my thesis consists of 75,746 words, inclusive of footnotes, but

exclusive of appendices and bibliography.

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Abstract

Argentina’s early twentieth century is commonly portrayed as a ‘golden age’ in

which it became ‘one of the richest countries in the world’. Here, however, this

optimistic vision is challenged by placing Argentina within a new metanarrative of

global divergence during the long nineteenth century. A massive terms-of-trade

boom – the extent of which has not previously been appreciated – had profoundly

uneven impacts across the periphery. Where land was abundant, frontiers could

expand, leading to dramatic extensive (that is, aggregate) growth. An expanding

frontier then had a safety-valve effect on labour markets, so capitalists responded to

high wages by mechanising production, which raised labour productivity and,

consequently, per capita incomes. In the land-scarce periphery, by contrast, deindus-

trialisation led to increasing quantities of labour receiving diminishing returns by

being applied to limited land resources. Similarly, Argentina’s own century-long

terms-of-trade boom allowed the Littoral to prosper but made the more densely

populated interior stagnate. The presence of the poor interior then prevented the

country from developing the kind of white-egalitarian democracy that had allowed

the prosperous European offshoots to make the transition to rapid intensive (that is,

per capita) growth. Most importantly, Argentina’s political backwardness ensured

that landownership remained concentrated, which muted the safety-valve effect of

the expanding frontier, so capitalists did not make the same investments in labour-

saving technologies. The new metanarrative of global divergence thus leads to a far

more pessimistic revision of Argentina at the beginning of the twentieth century – a

revision that is verified through a comparative assessment of its living standards that

shows them to have been considerably below the levels of Northern Europe and the

European offshoots. Argentina’s ‘golden age’ is therefore a myth.

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To Ron, Sally, Karen, y la changuita.

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Acknowledgements

Research for this dissertation received financial support from the Economic and

Social Research Council. Colin Lewis was instrumental in my obtaining that funding,

and provided patient supervision throughout my time at the LSE; Chris Minns came

on board later as a second supervisor, and gave much useful advice; Max-Stephan

Schulze excelled first as the PhD Programme Director, then as Head of Department;

and Rose Harris in the Financial Office gave assistance at various times, especially

when she rescued me from one particularly sticky situation.

The dissertation, especially Chapter 2, benefited greatly from comments

made by participants in the LSE Economic History Department’s Thesis Workshop,

particularly Peter Sims. Alejandra Irigoin kindly invited me to participate at the New

Economic Historians of Latin America workshop at the LSE on 26 April 2013, where

I received valuable feedback on Chapter 5, above all from Alfonso Herranz-Loncan.

Chapter 5 also benefited from being presented at the Oxford Economic & Social

History Graduate Workshop at Nuffield College on 6 November 2013.

Invaluable stimulation and support also came from Carlos Brando, Ulaş

Karakoç, Cecilia Lanata Briones, Jesús Emilio Monzón, Felipe Pereira Loureiro,

José Luis Quintana Goyeneche, Beatriz Rodriguez-Satizabal, Gerardo Serra,

Leonardo Weller, and Bernardo Wjuniski. In Argentina I am indebted to the kindness

of Jorge Gaggero, Juan Carlos Garavaglia, Norma Lanciotti, Marcelo Rougier, Ruth

Sautu, and the late Jorge Schvarzer, as well as the librarians of the Instituto Torcuato

di Tella, the Ministerio de Economía, and the Universidad de San Andrés. Elsewhere,

thanks must be given to Cristián Ducoing Ruiz, Manuel Llorca-Jaña, Jonathan

Nitzan, Jeffrey Williamson, and the staff of the Bodleian Library, the British Library,

the British Library of Political and Economic Science, and Senate House Library.

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Contents

Declaration 2........................................................................................................Abstract 3.............................................................................................................Acknowledgements 5...........................................................................................Contents 6.............................................................................................................Illustrations 8........................................................................................................

1. Introduction 11....................................................................................................From Pessimism to Optimism 13.........................................................................Pessimism Redux 19.............................................................................................

The Terms of Trade 20.....................................................................................The Great Divergences 23...............................................................................From Disorder to Order 27.............................................................................The Development Gap 37................................................................................Numbers, Myths, Metanarratives 39...............................................................

Appendix 1.1: Argentina’s GDP, 1800-2012 40...................................................The Official Estimates, 1935-2012 41.............................................................The Unofficial Extensions, 1800-1935 44.......................................................

2. The Long Boom 56..............................................................................................Old and New Narratives 57..................................................................................

The Prebisch-Singer Hypothesis 57................................................................Williamson’s Narrative 60...............................................................................

The Downward Bias 64........................................................................................India’s Deindustrialisation 80...............................................................................Whither Ricardo? 84.............................................................................................Appendix 2.1: 21 Terms-of-Trade Estimates, 1750-1913 85...............................Appendix 2.2: India’s Terms of Trade, 1861-1913 91..........................................

3. A New Order 96..................................................................................................Land and Growth 97.............................................................................................

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The United States 100......................................................................................The Followers 109...........................................................................................

The Land-Scarce Regions 113..............................................................................The Global Reordering 121..................................................................................Appendix 3.1: Land and Population in 166 Countries 123..................................

4. Reordering the River Plate 126.........................................................................The Imperial Impact 127......................................................................................Native Forces 136.................................................................................................

The Civil Wars 137..........................................................................................The Oligarchic State 146.................................................................................The Emerging Nation 157................................................................................

Paradise Gained? 172...........................................................................................Appendix 4.1: Argentina’s Terms of Trade, 1780-1938 174................................

Exchange Rates 175........................................................................................Wholesale Prices of Hides 176........................................................................The Export Price Index 181.............................................................................A Proxy Import Price Index 187......................................................................Results 189......................................................................................................

5. The ‘Golden Age’ Myth 193...............................................................................Living Standards 194............................................................................................

Political Institutions 194.................................................................................Public Welfare 200...........................................................................................National Income 208.......................................................................................

Paradise Lost? 221................................................................................................Appendix 5.1: International Price Levels, c. 1905-07 222...................................

Food Prices 223..............................................................................................Rents 225.........................................................................................................The Price Levels 228.......................................................................................

6. Conclusion 233....................................................................................................The Bigger Picture 236.........................................................................................

Data Appendix 240...............................................................................................Bibliography 309..................................................................................................

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Illustrations

FiguresA1.1 Argentina’s Relative GDP Per Capita, 1930-85 44.........................................A1.2 Argentina’s Relative GDP Per Capita, 1800-1913 54.....................................2.1 Williamson’s Terms-of-Trade Boom, 1800-1913 61.......................................2.2 Prices of an Internationally-Traded Good with Falling Trade Costs 67..........2.3 Price of Egyptian Cotton in Alexandria and Liverpool, 1824-1889 68...........2.4 Own-Price and Proxy Terms of Trade, 1860s-1913 70...................................2.5 Indonesia’s Own-Price Terms of Trade, 1825-1913 73...................................2.6 Prices in Britain and Indonesia, 1836-1913 75...............................................2.7 Two-Good Terms of Trade for Indonesia, 1836-1913 76................................2.8 Other Two-Good Terms of Trade for Indonesia, 1836-1913 77......................2.9 Freight-Rate Indices, 1800-1913 79................................................................2.10 Three Estimates of India’s Terms of Trade 82.................................................2.11 Terms of Trade for Cotton and Cotton Shirtings in India, 1815-1913 83.......3.1 Arable Potential and Population Growth, 1500-1900 101..............................3.2 US Terms of Trade, 1659-1913 105................................................................3.3 US Overseas Trade, 1790-1913 109................................................................3.4 Railway Density, 1830-1910 110....................................................................3.5 Arable Potential Realised, 1780-1910 111......................................................3.6 Welfare Ratios of Unskilled Labourers in Eurasia, 1730-1913 116................A3.1 Argentina’s Population, 1500-1900 125..........................................................4.1 Part-Proxy Terms of Trade for Nine Argentine Exports, 1780-1913 133........4.2 Part-Proxy Terms of Trade for Argentina, 1780-1913 135..............................4.3 Volatility in Argentina’s Part-Proxy Terms of Trade, 1780-1913 136.............4.4 Immigration and British Investment in Argentina, 1865-1913 149.................4.5 Land Distribution in 16 Counties of Buenos Aires Province, 1836-90 163....4.6 Cultivated Land Per Capita in Argentina, 1872-1913 164..............................4.7 Land Distribution in Argentina, 1914 165.......................................................

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A4.1 Prices of Bulls and Dry Hides in Buenos Aires, 1780-1848 179....................A4.2 Two Series of Salted Hide Prices, 1864-1906 180..........................................A4.3 Argentine Dry Hide Prices, 1780-1938 182....................................................A4.4 Argentine Salted Hide Prices, 1821-1938 183................................................A4.5 Two Export Price Indices for Argentina, 1864-1938 187................................A4.6 New and Old Terms-of-Trade Estimates for Argentina, 1810-1938 189........A4.7 Terms of Trade for Argentina and Indonesia, 1780-1938 191.........................5.1 Disproportional Representation in Argentina, 1895 and 1914 198.................5.2 International Life Expectancy at Birth, 1870-1913 204..................................5.3 International Primary School Enrolment, 1870-1913 206..............................

TablesA1.1 Three Estimates of Argentina’s GDP Growth, 1875-1913 46.........................A1.2 Cortés Conde’s Industrial Growth Rates for Argentina, 1875-1910 48..........A1.3 Argentine Production Tax Data for Beer, 1891-1900 50.................................A1.4 Argentine Production Tax Data for Wine, 1892-1900 51................................A1.5 Evidence of Industrial Growth in Argentina, 1870s-1913 52..........................2.1 Distribution of World Manufacturing Output, 1750-1913 63.........................2.2 Own-Price and Proxy Terms of Trade 71........................................................2.3 Williamson’s 21 Terms-of-Trade Series 72.....................................................2.4 Indonesia’s Two-Good Terms of Trade, 1836-1913 78...................................2.5 Cotton Cloth Production in India, 1795-1900 81............................................A2.1 Weights in India’s Import Price Index 92........................................................A2.2 Weights in India’s Export Price Index 93........................................................3.1 Global Arable Potential, 1780-1910 99...........................................................3.2 Welfare Ratios of Unskilled Labourers Around the World, 1500-1849 103...4.1 British Capital Exports, 1865-1913 150..........................................................4.2 Argentina’s Population, 1869-1914 159..........................................................4.3 Argentina’s Day Labourers, 1869-1914 161...................................................4.4 Argentina’s Textile Workers, 1869-1914 169..................................................A4.1 Weights in Argentina’s Export Price Index, 1780-1938 184...........................A4.2 Weights in Argentina’s Proxy Import Price Index, 1780-1938 188.................A4.3 Three Estimates of Argentina’s Terms of Trade, 1780s-1900s 190.................5.1 International Political Indicators, 1913 195....................................................5.2 International Health Indicators, c. 1909-13 201..............................................5.3 Life Expectancy at Birth in Argentina, 1913-15 202.......................................5.4 International Education Indicators, 1910 205.................................................

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5.5 International GDP Per Capita, 1913 209.........................................................5.6 International Real Wages, pre-First World War 211........................................5.7 International Weekly Wages in Construction, c.1905-09 212.........................5.8 International Prices, c. 1905-09 217................................................................5.9 International Price Levels, c. 1905-09 218......................................................5.10 International Wage Levels in Construction, c. 1905-09 219...........................A5.1 International Prices (Raw), c. 1905-09 224.....................................................A5.2 Cortés Conde’s Rent Series, 1903-12 226.......................................................A5.3 Rents in 23 Conventillos in Buenos Aires, 1907 227......................................A5.4 Rents in Buenos Aires, 1914 228....................................................................A5.5 Expenditure Shares on Five Food Items 229...................................................A5.6 Cost of Calories and Food Baskets 230...........................................................A5.7 Alternative Estimates of the Price Levels 232................................................A5.8 Correlation Coefficients of Price-Level Estimates 232...................................DA.1 Argentina’s GDP Estimates, 1875-2012 241...................................................DA.2 Williamson’s Terms-of-Trade Series, 1750-1913 247.....................................DA.3 Terms-of-Trade Series for Six Countries, 1861-1913 254..............................DA.4 Indonesia’s Terms of Trade, 1820-1913 256...................................................DA.5 India’s Terms of Trade, 1861-1913 258...........................................................DA.6 International Exchange Rates, 1791-1938 260................................................DA.7 International Commodity Prices, 1813-1913 264...........................................DA.8 International Freight Rates, 1757-1913 267....................................................DA.9 Arable Potential, Cropland, and Population, 1780-1910 269..........................DA.10 Potential Arable Land and World Population, 1500-1900 273........................DA.11 Estimated Exchange Rates for Argentina, 1780-1938 277..............................DA.12 Argentine Hide Prices in the Core (£ Per Ton), 1790-1938 281.....................DA.13 Hide Prices in Buenos Aires, 1780-1851 285..................................................DA.14 Hide Prices in Buenos Aires, 1863-1938 288..................................................DA.15 Argentina’s Export Prices, 1780-1938 291......................................................DA.16 Argentina’s Export Prices, 1910-1938 297......................................................DA.17 Argentina’s Proxy Import Price Index, 1780-1938 299..................................DA.18 The 100 Largest Corporations Registered in Argentina, 1914 303.................DA.19 Land Ownership in Buenos Aires Province, 1836-90 306..............................

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Chapter 1

Introduction

I believe that free trade is fatal to the nation. I shall never be able to understand howrestrictions on trade could constitute an obstacle to industry.

Pedro Ferré, Memorias1

To limit or restrict the entry of desirable products from abroad, so as to enhance theprice of inferior home products, is like debarring good-looking foreign women fromentering the country, in order that ill-favoured ones may make better marriages; it islike hindering people of rosy and clear complexions from entering, because themulattoes, who form the bulk of the nation, will be avoided by the women onaccount of their inferiority in looks.

Juan Bautista Alberdi, The Crime of War2

This dissertation analyses how global capitalism shaped Argentina through a boom in

its terms of trade during the long nineteenth century. In doing so, it places the coun-

try’s development within a broader metanarrative of the ‘great divergence’ between

poor and rich countries.3 During the long nineteenth century, the dissertation argues,

trade liberalisation, falling transportation costs, and increasing industrial productivity

in the North Atlantic core brought a massive, periphery-wide terms-of-trade boom

that radically reordered the world. In response to changes in relative prices, a new

global capitalist order formed in which the periphery specialised in primary-

commodity production, while the North Atlantic core industrialised. Land-abundant

regions more than anywhere else prospered from this new order, whereas land-scarce

regions that did not industrialise – or were deindustrialised – lost out. These global

1. Quoted in A.G. Frank, Lumpenbourgeoisie, Lumpendevelopment: Dependence, Class, and Polit-ics in Latin America, New York, 1972, p. 54.

2. J.B. Alberdi, The Crime of War, London, 1913, p. 241.3. To clarify, a metanarrative is an overarching framework for understanding something. On the

metanarratives of the great divergence, see P.K. O’Brien, ‘Metanarratives in Global Histories ofMaterial Progress’, International History Review, 23:2, 2001; and idem, ‘Ten Years of Debate onthe Origins of the Great Divergence’, Reviews in History, 1008, 2010, online at http://www.history.ac.uk/reviews/review/1008 (accessed 5 September 2013).

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processes of uneven development, as will be seen here, were also at work within

Argentina, preventing it from becoming one of the world’s most developed countries

despite its substantial land resources.

In arguing against the optimistic vision of Argentina’s long nineteenth century

that currently reigns in the historiography, this dissertation revisits some of the more

pessimistic conclusions that once predominated. It reinforces them with new and

under-utilised quantitative data, and by applying quality controls to the data that

optimists have used to make their case. Far too much of the optimistic histor-

iography, it contends, suffers from what D.C.M. Platt identified as the problem of

‘Mickey Mouse numbers’,4 as the optimists have too often relied on statistics of

dubious quality, especially unreliable estimates of gross domestic product (GDP).5

This dissertation, by contrast, will only use numbers that have passed some basic

controls for quality. Hence, unlike in much of the recent literature on Argentina, as

well as in the so-called New Economic History more broadly, here bad numbers will

not be preferred to no numbers at all.6 What reliable numbers there are, it will be

seen, support a more pessimistic revision of Argentina’s long nineteenth century.

4. D.C.M. Platt, Mickey Mouse Numbers in World History: The Short View, Basingstoke, 1989.5. This problem was pointed out some time ago in L. Randall, ‘Lies, Damn Lies, and Argentine

GDP’, Latin American Research Review, 11:1, 1976; since then, it has gotten worse, as will bedetailed at length in Appendix 1.1.

6. The determination of New Economic Historians (or ‘cliometricians’) to use numbers – almostany numbers – stems from a research agenda based on using quantitative methods (ofteneconometrics) to test hypotheses derived from neo-classical economic theory. N.F.R. Crafts,‘Cliometrics, 1971-1986: A Survey’, Journal of Applied Econometrics, 2:3, 1987. The problemswith this research agenda are at least twofold. First, it can lead to conclusions that are presentedas if they were historical facts, when their conclusions are actually dependent upon the assump-tions in the theories that underlie their models. Second, econometric models and the data fed intothem can be tweaked until they arrive at a statistically significant result that suits the researcher.For a description of this aspect of econometrics by a leading practitioner, see E.E. Leamer, ‘Let’sTake the Con Out of Econometrics’, American Economic Review, 73:1, 1983; and idem., ‘Tant-alus on the Road to Asymptopia’, Journal of Economic Perspectives, 24:2, 2010. For a usefuldemonstration of how this basic flaw can lead to different groups of econometricians reachingopposed results using the same data, see J.R. Magnus and M.S. Morgan, eds., Methodology andTacit Knowledge: Two Experiments in Econometrics, New York, 1999, chs. 1-14. Making theseproblems even worse, New Economic Historians have often proved resistant to new theories. Inthe words of one of their pioneers, Douglass North, ‘the limitations of neoclassical theory as atool kit are today more appreciated by many in economics – where I think a revolution is goingon – than in economic history, which tends to be more reactionary in terms of theoretical innova-tion than economics. And until economic historians break out of the strictures imposed byneoclassical theory, cliometrics will remain a relatively uninteresting field’. In G.D. Libecap, J.S.Lyons, and S.H. Williamson, ‘Douglass C. North’, in J.S. Lyons, L.P. Cain, and S.H. Williamson,eds., Reflections on the Cliometric Revolution: Conversations with Economic Historians,London, 2008, p. 197. Being uncharitable, it could be argued that the New Economic History hasbecome primarily concerned with verifying outmoded theories with dubious data using methodo-logies that are open to manipulation.

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The remainder of this introduction provides an overview of the dissertation,

placing its findings within their historiographical context. It begins by describing the

swing from pessimism to optimism in the historiography of Argentina’s long nine-

teenth century, highlighting the role that this swing has played in legitimising global

capitalism. Argentina has, it observes, been held up as one of the great success stories

of the ‘first globalisation’, and its subsequent decline is alleged to have been due to it

becoming more closed to the rest of the world. The remainder of the introduction

then provides a chapter-by-chapter summary of how the dissertation casts doubt on

this morality tale by demonstrating that its starting point is wrong: there was, the

dissertation will contend, no ‘golden age’ for Argentina at the beginning of the twen-

tieth century; rather, a long terms-of-trade boom had allowed some regions to

prosper, but had also made others stagnate, leading to an unevenness that prevented

Argentina from realising its potential as a land-abundant country.

From Pessimism to OptimismThe current optimism about Argentina at the beginning of the twentieth century is in

stark contrast to the pessimistic consensus that once reigned in the country’s histor-

iography. Drawing on ‘revisionist’ diatribes against foreign domination, which had

proliferated in the interwar period,7 as well as ‘structuralism’, the post-war critique of

neo-classical economic theory,8 in the 1960s and ‘70s most historians believed that

Argentina had missed an important opportunity in the long nineteenth century

because its rapid growth had been unbalanced and had not laid the foundations for

more long-term development. This pessimistic vision was shared by proponents of

‘modernisation theory’ and ‘dependency theory’ alike, with the more optimistic view

of liberals (in the Adam Smith sense) an uninfluential minority.9 Nevertheless, by the

7. See T. Halperín Donghi, El revisionismo histórico argentino, Buenos Aires, 1970; and idem, LaArgentina y la tormenta del mundo: Ideas y ideologías entre 1930 y 1945, Buenos Aires, 2003,ch. 2.

8. See J.L. Love, ‘The Rise and Fall of Structuralism’, in V. FitzGerald and R. Thorp, eds., Econ-omic Doctrines in Latin America: Origins, Embedding and Evolution, Basingstoke and NewYork, 2005; and R. Grosfoguel, ‘From Cepalismo to Neoliberalism: A World-Systems Approachto Conceptual Shifts in Latin America’, Review (Fernand Braudel Center), 19:2, 1996. Its theor-etical content is described in C. Kay, Latin American Theories of Development and Underdevel-opment, London, 1989, ch. 2; and O. Rodríguez, El estructuralismo latinoamericano, México,2006. For comparisons with the somewhat tamer ‘neo-structuralism’ of today, see F.I. Leiva,Latin American Neostructuralism: The Contradictions of Post-Neoliberal Development, Minnea-polis, 2008.

9. For a classic pessimistic analysis from the perspective of modernisation theory, see G. di Tella

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end of the twentieth century the pendulum had decisively swung toward a far more

optimistic vision, according to which Argentina had been a successful case of

‘export-led development’.10 Here this swing from pessimism to optimism will be

outlined.

The pessimists who once ruled in the historiography pointed towards the

country’s great regional disparities, its inegalitarian distribution of wealth and

income, and its vulnerability to fluctuations in international trade and capital flows.

Aldo Ferrer’s The Argentine Economy, first published in 1963, was the most

complete expression of this pessimistic vision.11 In an analysis of the country’s devel-

opment since colonisation, Ferrer argued that during the nineteenth century technolo-

gical change, particularly improved shipping and railways, drove the country’s integ-

ration into the world economy. The land-abundant Pampean zone prospered as a

result, as, in his words, the ‘useless territories of the colonial period [...] became the

nucleus of a rapid process of development’,12 but at the same time integration

brought deindustrialisation to the country’s interior,13 while the concentration of

landownership meant that even in the Pampean zone there was widespread underem-

ployment, which depressed living standards.14 The country’s export-led growth was,

moreover, vulnerable to its external position, especially because it was heavily

dependent upon imports for its supply of manufactured goods, so fluctuations in the

and M. Zymelman, Las etapas del desarrollo económico argentino, Buenos Aires, 1973, ch. 2.The key structuralist/dependentista account was A. Ferrer, The Argentine Economy, Berkeley,1967, chs. 5-12. For useful comparisons of the two theories, see J.S. Valenzuela and A. Valen-zuela, ‘Modernization and Dependency: Alternative Perspectives in the Study of Latin AmericanUnderdevelopment’, Comparative Politics, 10:4, 1978; and R. Grosfoguel, ‘Developmentalism,Modernity, and Dependency Theory in Latin America’, Nepantla: Views from the South, 1:2,2000. An important example of the liberal view from that era is F. Pinedo, La Argentina: Su posi-ción y rango en el mundo, Buenos Aires, 1971; also see J.A. Martínez de Hoz, La agricultura yla ganadería argentina en el período 1930-1960, Buenos Aires, 1967.

10. For overviews of this shift in the historiography, see E.J. Míguez, ‘La expansión agraria de lapampa humeda (1850-1914): Tendencias recientes de su análisis histórico’, Anuario IEHS, 1;idem, ‘¿Veinte años no es nada? Balance y perspectivas de la producción reciente sobre la granexpansión agraria, 1850–1914’, in J. Gelman, ed., La historia económica argentina en la encru-cijada, Buenos Aires, 2006; and R. Cortés Conde, ‘Export-Led Growth in Latin America:1870-1930’, Journal of Latin American Studies, 24, Quincentenary Supplement, 1992, pp.168-72.

11. A. Ferrer, La economía argentina: Las etapas de su desarrollo y problemas actuales, México,1963; and idem, Argentine Economy. The original was substantially revised and expanded in A.Ferrer, La economía argentina: Desde sus orígenes hasta principios del siglo XXI, 3rd ed.,Buenos Aires, 2004.

12. Ferrer, Argentine Economy, p. 77.13. Ibid., p. 241.14. Ibid., p. 116.

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terms of trade, a bad harvest, or an interruption of capital inflows could have

severely negative consequences for growth.15

A similarly pessimistic interpretation was offered by those following the prin-

ciples of modernisation theory. The case of Roberto Cortés Conde is particularly

notable because he would subsequently become the most prominent optimist, produ-

cing influential accounts of Argentina’s progress in the late nineteenth and early

twentieth centuries.16 In the mid-1960s, by contrast, he had reflected the consensus

that Argentina’s rapid growth prior to the First World War had represented a missed

opportunity.17 External circumstances, he claimed, had been highly favourable for the

country, allowing it to prosper by bringing new land into production through a rapid

expansion of the frontier. Yet this extensive growth was limited by the closing of the

frontier, while it was also vulnerable to changes in the external environment, espe-

cially given that the country had failed to industrialise. The result, Cortés Conde

concluded, was that Argentina’s apparent prosperity was more illusion than reality.

He wrote:

Testimonies of the time speak clearly enough of the sudden luxury of the untilrecently austere society of the River Plate; the ostentatious buildings and a way oflife that came close to the [...] richest and most sophisticated capitals of Europe. Inthat cultural life, in contrast to other countries in the world’s periphery, it was notjust the educated native-born elite that participated. [...] This fact created the impres-sion that [Argentina] had reached the levels of the most progressive and industrial-ised countries, and to some extent it had: a European population, extensive educa-tion, urban centres, such as Buenos Aires, that had little to envy in those of oldEurope. Yet something was lacking. Behind the advanced urban Argentina was avirtually pastoral society. There was no correlate industrial development. Whencircumstances changed and the external impetus disappeared, we found that thecastle had been built on air.18

15. Ibid., pp. 102-03, 122.16. R. Cortés Conde, El progreso argentino: 1880-1914, Buenos Aires, 1979; idem, ‘The Export

Economy of Argentina 1880-1920’, in idem and S.J. Hunt, eds., The Latin American Economies:Growth and the Export Sector 1880-1930, New York, 1985; R. Cortés Conde, ‘The Growth of theArgentine Economy, c. 1870-1914’, in L. Bethall, ed., The Cambridge History of Latin America,V, c. 1870-1930, Cambridge, 1986; R. Cortés Conde, La economía argentina en el largo plazo:Ensayos de historia económica de los siglos XIX y XX, Buenos Aires, 1997; and idem, ‘TheVicissitudes of an Exporting Economy: Argentina (1975-1930)’, in E. Cárdenas, J.A. Ocampo,and R. Thorp, eds., An Economic History of Twentieth-Century Latin America, I, The Export Age,Oxford, 2000.

17. R. Cortés Conde, ‘El ‘boom’ argentino: ¿Una oportunidad desperdiciada?’, in T. di Tella and T.Halperín Donghi, eds., Los fragmentos del poder, Buenos Aires, 1969; also see idem, ‘Problemasdel crecimiento industrial de la Argentina (1870-1914)’, Desarrollo Económico, 3:1/2, 1963; andE. Gallo and R. Cortés Conde, La formación de la Argentina moderna, Buenos Aires, 1967.

18. Cortés Conde, ‘‘Boom’ argentino’, p. 241, author’s translation.

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For many, including Cortés Conde,19 this pessimistic narrative began to

change through exposure to ‘staple theory’. Following the pioneering work of Harold

Innis,20 Canadian historians had argued that the rapid expansion of their country’s

export sector in the nineteenth century had generated linkages with other sectors,

leading to more broad-based growth, including industrialisation.21 In a highly influ-

ential study, Carlos Díaz Alejandro claimed that Argentina’s nineteenth-century

growth had fitted this pattern22 – a claim that Ezequiel Gallo reinforced with his

observation that industry had also grown rapidly at the beginning of the twentieth

century, in the midst of the export sector’s great expansion.23 Finally, Jonathan

Brown extended staple theory back to the late colonial era by maintaining that

increasing exports of silver from Potosí in Upper Peru triggered a pastoral expansion

on the Pampas, which then, as described by Díaz Alejandro and Gallo, turned into far

more broad-based growth after the arrival of the railways.24 As Brown summarised:

Both the export of foodstuffs to Upper Peru and the silver trade out of Potosíprovided the rationale for European settlement and commercial development in theRío de la Plata. Buenos Aires’ connection with Atlantic shipping, established by theillegal silver trade, eventually fostered the pastoral industries of the Litoral. Then,the European and North American revolutions in manufacturing of the first half ofthe nineteenth century further stimulated rural production in the region, and exportsof hides, wool, and a variety of pastoral goods more than replaced the deterioratingtrade through the port. Ranching, marketing, and processing – despite the limitationsof traditional technology – all expanded to support the export sector. Finally, themodern technology let loose by the industrial revolution reached the Río de la Platain the years following 1860. Existing trends in population growth, settlement of

19. For example, Cortés Conde, ‘Export-Led Growth’, pp. 170-71. Cf. idem, ‘Growth of the Argen-tine’, p. 355.

20. H. Innis, Essays in Canadian Economic History, Toronto, 1956.21. The first statement came from M.H. Watkins, ‘A Staple Theory of Economic Growth’, Canadian

Journal of Economics and Political Science, 29:2, 1963; cf. idem, ‘Staples Redux’, Studies inPolitical Economy, 79, 2007. Major subsequent contributions were A.O. Hirschman, ‘A General-ized Linkage Approach to Development, with Special Reference to Staples’, Economic Develop-ment and Cultural Change, 25, Supplement, 1977; G. di Tella, ‘The Economics of the Frontier’,in C.P. Kindleberger, ed., Economics in the Long View: Essays in Honour of WW Rostow, I,Models and Methodology, New York, 1982; R. Findlay and M. Lundahl, ‘Natural Resources,‘Vent-for-Surplus’, and the Staples Theory’, in G.M. Meier, ed., From Classical Economics toDevelopment Economics, Basingstoke and New York, 1994; and M. Altman, ‘Staple Theory andExport-Led Growth: Constructing Differential Growth’, Australian Economic History Review,43:3, 2003.

22. C.F. Díaz Alejandro, Essays on the Economic History of the Argentine Republic, New Haven,1970, pp. 9-11.

23. E. Gallo, ‘Agrarian Expansion and Industrial Development in Argentina’, in R. Carr, ed., LatinAmerican Affairs, Oxford, 1970. A similar argument was made around the same time by L.Geller, ‘El crecimiento industrial argentino hasta 1914 y la teoría del bien primario exportable’,Trimestre Económico, 37:148(4), 1970.

24. J.A. Brown, A Socioeconomic History of Argentina, 1776-1860, Cambridge, 1979.

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virgin territories, and expansion of the domestic market quickened. New technology,even though controlled by foreigners, extended economic activity to the Interior andbroadened Argentina’s exports. It proved the catalyst for continuing growth and ulti-mately for industrialization.25

Considerably later, Cortés Conde would reinforce this optimistic narrative by

providing numbers that verified the claim that rapid industrialisation had occurred

alongside export expansion. His new estimates of Argentina’s GDP showed industry

growing at a phenomenal trend rate of nine percent per year during 1875-1913, help-

ing drive an overall growth rate of seven percent.26 This finding was crucial because

the historiography had previously reached an impasse between pessimism and optim-

ism due to the lack of data. As a literature review published shortly before Cortés

Conde released his numbers explained:

[T]he discussion ceased before it had finished, probably because it could only go onproducing more of the same arguments with the tools available. Thus the estimatesof the economic indicators on which many of these studies were based were notrevised. Nor did researchers undertake a search of the primary sources that wouldhave allowed them to line up new evidence.27

Cortés Conde’s new numbers showing dramatic industrial growth accordingly had a

major impact. They inspired other studies of Argentina’s industrialisation that typic-

ally drew on far more fragmentary data, but could still point toward Cortés Conde’s

numbers to demonstrate the rapid growth that they were describing.28 Few, however,

25. Ibid., p. 233.26. Calculated from Cortés Conde, Economía argentina, pp. 230-31, Cuadro A1. This is a mildly

revised version of the GDP estimates detailed in R. Cortés Conde, ‘Estimaciones del productobruto interno de Argentina 1875-1935’, Documento de Trabajo 3, Departamento de Economía yMatemática, Universidad de San Andres, 1994. See Appendix 1.1, pages 45-53, for details.

27. J.C. Korol and H. Sabato, ‘Incomplete Industrialization: An Argentine Obsession’, Latin Amer-ican Research Review, 25:1, 1990, pp. 23-24.

28. See F. Rocchi, Chimneys in the Desert: Industrialization in Argentina During the Export BoomYears, 1870-1930, Stanford, 2006, esp. pp. 21, 24-25, 42; and M.I. Barbero and F. Rocchi,‘Industry’, in G. della Paolera and A.M. Taylor, eds., A New Economic History of Argentina,Cambridge, 2003, esp. pp. 264-65; also Y. Pineda, Industrial Development in a FrontierEconomy: The Industrialization of Argentina, 1890-1930, Stanford, 2009. An example of the kindof fragmentary data these studies have mustered to support their case comes from Rocchi’s find-ing that 74 industrial companies received loans worth $17.2 million from the Banco de la Provin-cia de Buenos Aires during 1906-16, which he takes as evidence that there was no ‘anti-indus-trial’ bias in Argentina’s financial system (Chimneys in the Desert, pp. 252-54). Yet he fails toprovide any of the context that is necessary to understand these numbers; that, for instance, theseloans were just 1.4 percent of the bank’s total loans during this period (calculated from H.J.Cuccorese, Historia del Banco de la Provincia de Buenos Aires, Buenos Aires, 1972, Cuadro 27),and that more aggregated data suggest that the financial system was heavily oriented toward theneeds of merchants and especially large landowners. See, for example, J. Adelman, ‘Agricultural

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appear to have looked at the methodology underlying Cortés Conde’s series, nor,

vitally, did they attempt to replicate them. That task, which is undertaken in

Appendix 1.1,29 suggests they can only be reproduced if obvious methodological

errors are made. For example, Cortés Conde’s spectacular industrial growth rate of

12 percent per year in the 1890s appears to be due to a greater range of goods being

taxed by the government, which he seems to have mistaken for an increase in the

output of those goods. Nonetheless, as such checks have not previously been made,

Cortés Conde’s numbers have come to feature prominently in the more optimistic

accounts of Argentina’s nineteenth century, as they have led historians to conclude

that the rapidly rising incomes generated by export-led growth made the internal

market expand, leading to final demand linkages that drove dramatic industrialisa-

tion.30 Optimism, armed with Mickey Mouse numbers, has in this way prevailed.

This swing towards optimism has also had ramifications far beyond the

historiography of Argentina’s long nineteenth century. The belief that Argentina was

once ‘one of the richest countries in the world’, but then declined precipitously, has

become widespread, with a cottage industry emerging around the ‘Argentine para-

dox’ – a research agenda that attempts to explain how a rich country could have

subsequently become a relatively poor country.31 Typically, the answer given is some

variation on the following: at the beginning of the twentieth century Argentina exper-

ienced a ‘golden age’ when it prospered by being open to international flows of

Credit in the Province of Buenos Aires, Argentina, 1890-1914’, Journal of Latin American Stud-ies, 22:1, 1990, pp. 73-81.

29. See pages 47-53.30. F. Rocchi, ‘El péndulo de la riqueza: La economía argentina en el período 1880-1916’, in M.

Zaido Lobato, ed., Nueva historia argentina, V, El progreso, la modernización y sus límites(1880-1916), Buenos Aires, 2000; and R. Hora, Historia económica de la Argentina en el sigloXIX, Buenos Aires, 2010, ch. 7.

31. Major works that pursue this research agenda include Díaz Alejandro, Essays on the EconomicHistory; C. Waisman, Reversal of Development in Argentina: Postwar CounterrevolutionaryPolicies and Their Structural Consequences, Princeton, 1987; D. Cavallo, R. Domenech, and Y.Mundlak, La Argentina que pudo ser: Los costos de la represión económica, Buenos Aires, 1989;P.H. Lewis, The Crisis of Argentine Capitalism, Chapel Hill, 1990; A.M. Taylor, ‘ExternalDependence, Demographic Burdens, and Argentine Economic Decline After the Belle Époque’,Journal of Economic History, 52:4, 1992; P. Gerchunoff and L. Llach, El ciclo de la ilusión y eldesencanto: Un siglo de políticas económicas argentinas, Buenos Aires, 1997; R. Cortés Conde,Progreso y declinación de la economía argentina, 2nd ed., Buenos Aires, 1998; della Paolera andTaylor, eds., A New Economic History; and C.M. Lewis, Argentina: A Short History, Oxford,2002; and L.J. Alston and A.A. Gallo, ‘Electoral Fraud, the Rise of Perón and Demise of Checksand Balances in Argentina’, Explorations in Economic History, 47:2, 2010. A useful survey andinterpretation of some of the early Argentine-paradox literature is given in C.M. Lewis, ‘Explain-ing Economic Decline: A Review of Recent Debates in the Economic and Social History Literat-ure on the Argentine’, European Review of Latin American and Caribbean Studies, 64, 1998.

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goods, capital, and labour; following the First World War and/or the Great Depres-

sion, the country experienced some problems due to adverse external circumstances;

thereafter, it declined because its government was illiberal, turning its back on glob-

alisation.32 Argentina is thus held up as a prime example of what could happen to a

country if it rejects liberal principles by having an interventionist state that seeks to

direct its development. In this way, Argentina’s history has become one of the key

morality tales of the new global capitalist order. The moral of its sad tale is liberalise

or be damned.33

Pessimism ReduxThis dissertation demonstrates that the starting point for the Argentine morality tale –

the ‘once upon a time’ – is incorrect. The dissertation explains why Argentina’s

integration into global capitalism did not turn it into ‘one of the richest countries in

the world’. To be clear, capitalism is here defined as a mode of power in which soci-

ety is ordered (and reordered) by prices.34 Following the logic of this definition, the

dissertation analyses how global capitalism shaped Argentina through changes in the

relative prices of its exports and imports, or what are technically known as its ‘net

barter terms of trade’ (NBTT),35 which are calculated as follows:

NBTT Import price index

Export price index= 1.1

The dissertation argues that changes in this ratio reordered the world during the long

nineteenth century, as a long terms-of-trade boom drove divergence between an

industrialising North Atlantic core, the prosperous European offshoots, and the poor

periphery.36 Within Argentina, improved terms of trade led to highly uneven develop-

32. This is, in effect, the argument of Díaz Alejandro (Essays on the Economic History), who most ofthe subsequent ‘Argentine paradox’ literature has followed, while adding some nuance.

33. For a prominent example, see A. Beattie, False Economy: A Surprising Economic History of theWorld, New York, 2009, ch. 1.

34. This definition draws on J. Nitzan and S. Bichler, Capital as Power: A Study of Order andCreorder, London, 2009, esp. ch. 13.

35. For a comparison with the various other terms-of-trade concepts (‘gross barter’, ‘single factoral’,and ‘double factoral’), see C.P. Kindleberger, International Economics, 4th ed., Homewood,1968, pp. 73-76.

36. To clarify, the terms ‘periphery’ and ‘core’ are used in this dissertation in a geographic (and nine-teenth-century specific) sense, as the periphery is understood to be all of the world outside of theNorth Atlantic core, which in turn includes both northwestern Europe and the northeastern

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ment that combined prosperity, as described by the optimists, with stagnation, which

the pessimists were more conscious of. This, then, was the result of Argentina being

reordered by global capitalism – of being integrated, in other words, into a global

order in which power was exercised through the price system. The remainder of this

introduction will summarise how this analysis is advanced in this dissertation chapter

by chapter, with each placed within its historiographical context.

The Terms of TradeDebates about the terms of trade have long focused on Raúl Prebisch and Hans

Singer’s famous hypothesis that a long-term deterioration in the periphery’s terms of

trade undermined the liberal assumption that the periphery should specialise in the

production of primary commodities for export.37 In the subsequent debate, the main

question became whether this long-term deterioration had really taken place.38 The

consensus among historians, at least until recently, has been that there were no trends

in the terms of trade, only cyclical fluctuations. With regard to Latin America,

Stephen Haber neatly expressed this widespread belief:

[W]hen other scholars examined the terms-of-trade argument closely, by pushingestimates back into the nineteenth century and by subjecting the data to more carefulanalysis, they found that for long periods the terms of trade actually improved, evenduring the so-called era of export liberalism. The weight of the evidence points tothe conclusion that there has been no secular deterioration in Latin America's termsof trade, but rather there have been cyclical swings with no discernable long-termtrend.39

seaboard of the United States. From this perspective, for example, the North American West waspart of the periphery. The ‘European offshoots’ were the settler societies of Australasia and NorthAmerica.

37. R. Prebisch, ‘The Economic Development of Latin America and Its Principal Problems’, Econ-omic Bulletin for Latin America, 7:1, (1950) 1962; and H.W. Singer, ‘The Distribution of Gainsbetween Investing and Borrowing Countries’, American Economic Review, 40:2, 1950. On theorigins of their hypothesis, see J.L. Love, ‘Raúl Prebisch and the Origins of the Doctrine ofUnequal Exchange’, Latin American Research Review, 15:3, 1980; idem, Crafting the ThirdWorld: Theorizing Underdevelopment in Rumania and Brazil, Stanford, 1996, ch. 7; D.J. Shaw,Sir Hans Singer: The Life and Work of a Development Economist, Houndsmill and New York,2002, pp. 49-58; J. Toye and R. Toye, ‘The Origins and Interpretation of the Prebisch-SingerThesis’, History of Political Economy, 35:3, 2003; and E.J. Dosman, The Life and Times of RaúlPrebisch, 1901-1986, Montreal, 2008, chs. 5-11.

38. For overviews, see J. Spraos, Inequalising Trade? A Study of Traditional North/South Specialisa-tion in the Context of Terms of Trade Concepts, New York, 1983, ch. 3; D. Diakosavvas and P.L.Scandizzo, ‘Trends in the Terms of Trade of Primary Commodities, 1900-1982: The Controversyand Its Origins’, Economic Development and Cultural Change, 39:2, 1991, pp. 232-46; and J.A.Ocampo and M.A. Parra, ‘The Continuing Relevance of the Terms of Trade and IndustrializationDebates’, in E. Peréz Caldentey and M. Vernengo, eds., Ideas, Policies and Economic Develop-ment in the Americas, London, 2007, pp. 163-66.

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Given this consensus, Jeffrey Williamson’s recent work has been striking, in

that he has contended that there was a long-term boom in the periphery’s terms of

trade during the nineteenth century, and it was, moreover, of much significance for

the ‘great divergence’.40 He claims that the terms of trade improved due to the

combined effects of trade liberalisation, reduced transportation costs, and increasing

productivity in the core’s industry. The boom that followed, Williamson argues, then

led to deindustrialisation by undermining the periphery’s cottage industries, as it

pulled capital and labour towards the primary commodity-focused export sector.41

Divergence resulted because, in Williamson’s words, (1) ‘industrial-urban activities

contain far more cost-reducing and productivity-enhancing forces than do traditional

agriculture and traditional services’;42 (2) deindustrialisation led to a ‘resource curse’

that saw the periphery’s institutions come to reflect the interests of the rent-seeking

elites that were the principal beneficiaries of primary-commodity exports;43 and (3)

there was more growth-inhibiting volatility because primary-commodity prices fluc-

tuate more dramatically than those of manufactured goods.44 In this way, William-

son’s new terms-of-trade narrative has the long boom generating divergence by

dividing the world into an industrialised core and a poor, deindustrialised periphery

that was afflicted by bad institutions and great instability.45

39. S. Haber, ‘Introduction: Economic Growth and Latin American Economic Historiography’, inidem, ed., How Latin America Fell Behind: Essays on the Economic History of Brazil andMexico, Stanford, 1997, p. 12.

40. Most notably, J.G. Williamson, ‘Globalization and the Great Divergence: Terms of Trade Booms,Volatility and the Poor Periphery, 1782-1913’, European Review of Economic History, 12:3,2008; and idem, Trade and Poverty: When the Third World Fell Behind, Cambridge, MA, 2011;also see Y.S. Hadass and J.G. Williamson, ‘Terms-of-Trade Shocks and Economic Performance,1870-1940: Prebisch and Singer Revisited’, Economic Development and Cultural Change, 51:3,2003; J.G. Williamson, Globalization and the Poor Periphery before 1950, Cambridge, MA,2006, chs. 2, 3, and 5; and C. Blattman, J. Hwang, and J.G. Williamson, ‘Winners and Losers inthe Commodity Lottery: The Impact of Terms of Trade Growth and Volatility in the Periphery1870-1939’, Journal of Development Economics, 82:1, 2007. For an illustration of the influenceof Williamson’s arguments, see R.C. Allen, Global Economic History: A Very Short Introduction,Oxford, 2011, chs. 5-6.

41. Williamson defines industrialisation as ‘an increase in the share of economic activity based inindustry’. Williamson, Trade and Poverty, p. 49. Deindustrialisation is therefore a decreasingshare of industry in total productive activity – a definition that this dissertation follows.

42. Williamson, Trade and Poverty, p. 49.43. Ibid., pp. 50-51.44. Ibid., pp. 51-53, ch. 10.45. Exactly how original this narrative is is open to debate. Williamson identifies the work of W.

Arthur Lewis as a precursor. See Williamson, Trade and Poverty, p. 33). Lewis did not, however,identify the terms of trade as a driving force of deindustrialisation. Indeed, he believed that theperiphery’s factoral terms of trade deteriorated during the late nineteenth century. W.A. Lewis,The Evolution of the International Economic Order, Princeton, 1978, ch. 3; also see idem,

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Chapter 2 will greatly reinforce Williamson’s claim that there was a long

terms-of-trade boom, but only by criticising the evidence that Williamson himself

uses to illustrate it. This task is important because Williamson has been applauded for

assembling a database of the terms of trade of numerous peripheral countries; one

prominent reviewer, for example, states that a ‘major contribution of Williamson’s

research is the compilation of a data set on the terms of trade for 21 poor countries’.46

Yet Chapter 2 demonstrates that most of Williamson’s 21 series are of doubtful qual-

ity since they have been calculated by using prices from the core countries as proxies

for prices in the periphery. Given the massive price convergence that took place

during the nineteenth century, the result is a downward bias in the trends of these

estimates, which leads Williamson to greatly underestimate the length, magnitude,

and universality of the periphery’s terms-of-trade boom.47

By criticising Williamson’s empirical evidence for the long boom, Chapter 2

actually reinforces the link that he makes between the terms of trade and deindustri-

alisation. The explanatory power of Williamson’s narrative seems limited because he

did not detect any boom for India,48 even though it has been by far the most widely

discussed case of the periphery’s nineteenth-century deindustrialisation.49 Chapter 2,

however, shows that Williamson’s failure to find a boom for India was due to his use

of a ‘proxy’ estimate, whereas price data taken from India clearly indicate that its

terms of trade must have improved significantly. What Williamson sees as a para-

Aspects of Tropical Trade 1883-1965, Stockholm, 1969, pp. 17-25; and idem, Growth and Fluc-tuations 1870-1913, London, 1978, pp. 188-93. A predecessor that, on the other hand, is quiteclose to Williamson is M. Lévy-Leboyer, Les banques européenes et l’industrialisation interna-tionale dans la première motié du XIX siècle, Paris, 1964, ch. 4. Yet, as will be seen in Chapter 3,Lévy Leboyer did not see deindustrialisation as having any negative ramifications for the peri-phery’s development because he believed in the neo-classical model of international trade.

46. N. Crafts, ‘Book Review Feature: Trade and Poverty: When the Third World Fell Behind’, Econ-omic Journal, 123, 2013, p. F193.

47. It was this same faulty methodology that led Hans Singer to detect such a long-term seculardeterioration. His findings were first published in United Nations, Relative Prices of Exports andImports of Under-Developed Countries: A Study of Post-War Terms of Trade between Under-Developed and Industrialized Countries, Lake Success, 1949; and were partially reproduced inPrebisch, ‘Economic Development’, p. 4, Table 1.

48. T. Roy, ‘Review of Trade and Poverty: When the Third World Fell Behind’, EH.net, 2012, online:http://eh.net/book_reviews/trade-and-poverty-when-third-world-fell-behind (accessed 7 October2012).

49. For overviews, see I. Habib, ‘Studying a Colonial Economy – Without Perceiving Colonialism’,Modern Asian Studies, 19:3, 1985, pp. 359-64; T. Roy, Rethinking Economic Change in India:Labour and Livelihood, London and New York, 2005, ch. 5; and P. Parthasarathi, ‘HistoricalIssues of Deindustrialization in Nineteenth-Century South India’, in G. Riello and T. Roy, eds.,How India Clothed the World: The World of South Asian Textiles, 1500-1850, Leiden, 2009.

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dox – that India deindustrialised without a boom50 – thus ceases to be one once the

methodological issues discussed in Chapter 2 are taken into account. The periphery’s

long terms-of-trade boom has, then, far more explanatory power than even William-

son supposes.

The Great DivergencesChapter 3 goes beyond Williamson to explain why the long boom drove global diver-

gence. Much of the existing literature has tended to focus either on the divergence

between Asia and Europe,51 or on the divergence between Anglo and Latin America.52

Williamson himself offers a variation on this theme with his new terms-of-trade

narrative, as he seeks to explain the divergence between industrialising Europe and

the deindustrialising poor periphery, ignoring the prosperous European offshoots in

Australasia and North America. Why they are excluded can be seen by considering

some of the implications of these regions for Williamson’s narrative; taking them

into account begs a series of questions: Given that the European offshoots prospered

while exporting primary commodities, why were they not afflicted by the same

resource curse of rent-seeking elites as the poor periphery? Why were they able to

industrialise (to varying degrees), even as the land-scarce periphery experienced

deindustrialisation? Chapter 3 will seek to answer these questions by elaborating a

new metanarrative to understand both of the great nineteenth-century divergences.

To explain the rise of the land-abundant European offshoots, Chapter 3 draws

on some lessons from North America’s historiography. In land-abundant regions, it

argues, the long boom allowed frontiers to expand by making it profitable to bring

new land into production. This expanding frontier then acted as a ‘safety valve’ that

stopped labour markets from becoming saturated, so wages could remain high

despite the arrival of millions of immigrants. In North American social thought

observations of this safety-valve effect have a long tradition. It is most often associ-

ated with Frederick Jackson Turner’s late nineteenth-century ‘frontier thesis’,53

50. Williamson, Trade and Poverty, ch. 6.51. Notable examples are A.G. Frank, ReOrient: Global Economy in the Asian Age, Berkeley, 1998;

and K. Pomeranz, The Great Divergence: China, Europe, and the Making of the Modern WorldEconomy, Princeton, 2000.

52. Most notably, S.L. Engerman and K.L. Sokoloff, Economic Development in the Americas since1500: Endowments and Institutions, Cambridge, 2012.

53. F.J. Turner, The Frontier in American History, New York, 1920, esp. pp. 259-60, 280.

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although it can really be traced back to at least the eighteenth century.54 Initially it

was believed that the expanding frontier prevented social unrest, then economists

claimed that it kept wages high by permitting labour to move to the West, in that way

preventing more easterly labour markets from becoming saturated. Subsequent

debates revolved around the question of whether labourers could have afforded to

move westward to take up farming,55 and whether they did in fact move.56 The more

fundamental point, however, is that it did not matter who moved, as long as the fron-

tier was providing enough opportunities to keep draining labour from the East. As

Ellen von Nardroff explained in an important statement of the safety-valve concept,

‘[t]he safety valve effect did not necessarily depend upon Eastern laborers going

West to farms. [...] [I]t makes little difference’, she continued, ‘if any specified group

went West to do any one particular thing as long as somebody went West to do some-

thing which increased their productivity in relation to what it would have been in the

East and if a high wage level were maintained as a result’.57

It was this safety-valve effect of the expanding frontier, Chapter 3 continues,

that distinguished the European offshoots from the land-scarce regions of the world,

which were afflicted by what Arthur Lewis called ‘unlimited supplies of labour’.58

The two types of region, land abundant and land scarce, could therefore take quite

different developmental paths. As von Nardroff explained for the United States:

The effect of the frontier on the supply of labor to industry was due to the factor thathas been most obvious all along; namely, that the agricultural sector was expandingphysically. [...] [T]his is something of an anomaly in economic development. Bothin Europe and in the typical underdeveloped country today, initial industrial devel-opment was and is based on exploitation of an agricultural labor surplus, meaning

54. H.N. Smith, Virgin Land: The American West as Symbol and Myth, Cambridge, MA, 1950, ch.20.

55. C.H. Danhof, ‘Farm-Making Costs and the ‘Safety Valve’: 1850-60’, Journal of PoliticalEconomy, 49:3, 1941; R.E. Ankli, ‘Farm-Making Costs in the 1850s’, Agricultural History, 48:1,1974; and J. Atack, ‘Farm and Farm-Making Costs Revisited’, Agricultural History, 56:4, 1982.

56. J.W. Adams and A.B. Kasakoff, ‘Wealth and Migration in Massachusetts and Maine: 1771–1798’, Journal of Economic History, 45:2, 1985, pp. 363-68; J.P. Ferrie, ‘Migration to the Fron-tier in Mid-Nineteenth Century America: A Re-examination of Turner’s Safety Valve’, unpubl-ished paper, 1997, available online at http://faculty.wcas.northwestern.edu/~fe2r/papers/munich.pdf (accessed 19 November 2013); and J.I. Stewart, ‘Migration to the Agricultural Fron-tier and Wealth Accumulation, 1860–1870’, Explorations in Economic History, 43:4, 2006.

57. E. von Nardroff, ‘The American Frontier as a Safety Valve: The Life, Death, Reincarnation, andJustification of a Theory’, Agricultural History, 36:3, 1962, pp. 135-36; for the same point, seeH.J. Habakkuk, American and British Technology in the Nineteenth Century: The Search forLabour-Saving Inventions, Cambridge, 1962, pp. 11-12, fn. 2.

58. W.A. Lewis, ‘Economic Development with Unlimited Supplies of Labour’, Manchester School,22:2, 1954.

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that the marginal productivity of labor in agriculture is or is approaching zero, thatlabor already engaged in agriculture may be withdrawn without reducing the totalproduct of the sector significantly, and that the supply of labor to industry, for atime, at least, is infinitely elastic at subsistence wages. No such state of affairs everexisted in this country [...]. As a result, American industry was relatively capitalintensive from the start and continues to be so.59

This exceptionalism allowed the European offshoots to prosper, as the safety-valve

effect of the expanding frontier provided the bridge that turned the extensive (that is,

aggregate) growth predicted by staple theory into intensive (that is, per capita)

growth.60 As John Habakkuk famously argued, high wages meant that North Amer-

ican capitalists tried to reduce labour costs by investing in machinery and equip-

ment.61 For this reason, North American industry became highly mechanised, raising

levels of labour productivity and, consequently, per capita incomes.62

Chapter 3 contends that where land was scarce, by contrast, the long boom

produced quite opposite tendencies. As industry concentrated in the North Atlantic

59. Von Nardroff, ‘American Frontier’, pp. 138-39.60. Many have missed the point that staple theory does not predict intensive growth. On its own, it

merely predicts that the expansion of export staples will trigger the growth of non-export sectorsthrough a variety of ‘linkages’, which lead to ‘diversification around an export base’. Watkins,‘Staple Theory’, p. 144. Hence, ‘backward linkages’ encourage the domestic production of goodsused in the production of staples; ‘forward linkages’ promote secondary industries that processthem; ‘final-demand linkages’ stimulate the production of goods for the consumption of thoseengaged in staple production; and ‘fiscal linkages’ derive from governments spending the reven-ues that come from growth. See ibid., p. 145; idem, ‘Staples Redux’, p. 118; and Hirschman,‘Generalized Linkage Approach’, pp. 72-80. What staple theorists do not do, by their own admis-sion, is provide a theory of per capita growth. See J.H. Dales, J.C. McManus, and M.H. Watkins,‘Primary Products and Economic Growth: A Comment’, Journal of Political Economy, 75:6,1967.

61. On this connection, see Habakkuk, American and British Technology, esp. ch. 3. Given itsimportance to this dissertation, Habakkuk’s hypothesis should be defended from its main criti-cism, which is that the nominal value of capital per worker was perhaps 25 percent higher inBritain than in the United States in 1860, thereby indicating that Britain was actually more capitalintensive, even though it had a low land-labour ratio. A.J. Field, ‘On the Unimportance ofMachinery’, Explorations in Economic History, 22:4, 1985, p. 394, Table 5. While generallyaccepted, this critique suffers from a major empirical failing, in that it does not take into accountthe lower prices of capital goods in the United States. Hence, one highly approximate estimatesuggests that in 1870-74 they were 83 percent more expensive in Britain than in the UnitedStates. W.J. Collins and J.G. Williamson, ‘Capital-Goods Prices and Investment, 1870-1950’,Journal of Economic History, 61:1, 2001, p. 67, Table 2. If the price difference was the same in1860, it would indicate that, in ‘real’ terms, the capital stock per worker in the United States wasin fact 46 percent higher than in Britain. A confirmation of this comes from extrapolations backfrom post-Second World War estimates of the capital stock per worker at purchasing powerparity, which show the US level at 20 percent above the British level in 1870. A. Maddison,Phases of Capitalist Development, Oxford, 1982, p. 54, Table 3.5.

62. On the close relationship between ‘capital intensity’ and GDP per capita, see R.C. Allen, ‘Tech-nology and the Great Divergence: Global Economic Development since 1820’, Explorations inEconomic History, 49:1, 2012.

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core due to the head start given it by the industrial revolution,63 its ever-cheaper

manufactures undermined the periphery’s (import-competing) cottage industries,

which also saw the cost of their (exportable) raw materials go up due to the improved

terms of trade. Deindustrialisation then depressed living standards because, following

Lewis’ logic, diminishing returns set in when more labour was applied to a more or

less fixed supply of land.64 Massive underemployment resulted, leading to the situ-

ation described above by von Nardroff as that of the ‘typical underdeveloped coun-

try’. In Lewis’ words:

[A]n unlimited supply of labour may be said to exist in those countries where popu-lation is so large relatively to capital and natural resources, that there are large sect-ors of the economy where the marginal productivity of labour is negligible, zero, oreven negative. Several writers have drawn attention to the existence of such‘disguised’ unemployment in the agricultural sector, demonstrating in each case thatthe family holding is so small that if some members of the family obtained otheremployment the remaining members could cultivate the holding just as well [...].The phenomenon is not, however, by any means confined to the countryside.Another large sector to which it applies is the whole range of casual jobs – theworkers on the docks, the young men who rush forward asking to carry your bag asyou appear, the jobbing gardener, and the like. These occupations usually have amultiple of the number they need, each of them earning very small sums from occa-sional employment; frequently their number could be halved without reducingoutput in this sector.65

The growth in this pool of surplus labour due to deindustrialisation therefore reduced

average productivity levels by increasing the rate of underemployment.

In a nutshell, then, the metanarrative presented in Chapter 3 is that the long

boom had hugely uneven impacts on different regions, depending upon their endow-

ments of land and labour. Where land was abundant it allowed frontiers to expand,

63. The possible logic of this agglomeration is outlined in P. Krugman and A.J. Venables, ‘Globaliza-tion and the Inequality of Nations’, Quarterly Journal of Economics, 110:4, 1995; also see M.Fujita, P.R. Krugman, and A.J. Venables, The Spatial Economy: Cities, Regions and InternationalTrade, Cambridge, MA, 1999, chs. 14-17. For a notable, although not entirely satisfactory,attempt to apply Krugman and Venables’ model to history, see N. Crafts and A. Venables, ‘Glob-alization in History: A Geographical Perspective’, in M.D. Bordo, A.M. Taylor, and J.G. William-son, eds., Globalization in Historical Perspective, Chicago, 2003, pp. 331-36.

64. Lewis, ‘Economic Development’, pp. 140-55. Lewis was inspired in turn by Ricardo, who drewon Malthus. D. Ricardo, On the Principles of Political Economy and Taxation, 3rd ed., London,1821, ch. 5, in P. Sraffa, ed., The Works and Correspondence of David Ricardo, I, Indianapolis,(1951) 2004. Lewis’ updating of this ‘classical’ model would be criticised by ‘neo-classical’economists, but none of their criticisms have been entirely convincing. See G. Ranis, ‘Is DualismWorth Revisiting?’, in A. Janvry and R. Kanbur, eds., Poverty, Inequality and Development:Essays in Honor of Erik Thorbecke, I, Economic Studies in Inequality, Social Exclusion and Well-Being, New York, 2006, pp. 371-85.

65. Lewis, ‘Economic Development’, p. 141.

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which then acted as a safety valve that prevented labour markets from becoming

saturated despite rapid population growth. High wages then made capitalists invest in

labour-saving technologies, which raised average productivity levels. The long boom

accordingly turned the European offshoots into the world’s richest countries, even as

in the land-scarce periphery it had quite opposite effects. Outside the North Atlantic

core, where industry was agglomerating, improved terms of trade brought deindustri-

alisation by depressing the prices of manufactures and driving up the costs of raw

materials, thereby decreasing opportunities for employment outside of agriculture.

More labour was then applied to limited supplies of land, leading to the diminishing

returns that depressed average productivity levels. In this way, the metanarrative

outlined in Chapter 3 explains how the long boom allowed land-abundant regions to

prosper, while making land-scarce regions outside the North Atlantic core stagnate.

From Disorder to OrderThis new framework for understanding global divergence is applied to Argentina in

Chapter 4. The chapter’s most important empirical contribution is to show that there

was a massive improvement in Argentina’s terms of trade from independence up to

the First World War. In finding this, the chapter corrects a major methodological

error in the existing literature: historians have mainly looked at absolute rather than

relative prices, often drawing them, moreover, from the core countries, rather than

from Argentina itself. Tulio Halperín Donghi, in particular, pioneered this error in

two classic essays on Argentina’s pastoral expansion in the first half of the nineteenth

century.66 By examining the nominal prices of River Plate hides and tallow in Britain,

he found that they rose somewhat after independence, but then experienced a ‘slow

but very prolonged fall’ from the mid-1830s onward,67 precisely as hide and tallow

exports from Buenos Aires took off. This led Halperín Donghi to conclude that the

pastoral expansion was not due to price incentives because, as he put it, his numbers

‘perfectly demonstrate the economic climate in which pastoral production occurred

in the whole River Plate area (and, for that reason, also in the countryside of Buenos

66. T. Halperín Donghi, ‘La expansión ganadera en la campaña de Buenos Aires (1810-1852)’,Desarrollo Económico, 3:1/2, 1963; and idem, ‘La expansión de la frontera de Buenos Aires(1810-1852)’, in A. Jara, ed., Tierras nuevas: Expansión territorial y ocupación del suelo enAmérica (siglos xvi-xix), México, DF, 1969.

67. Halperín Donghi, ‘Expansión de la frontera’, p. 82, author’s translation.

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Aires); [it was] a production that did not receive its stimulus, nor see its momentum

hampered, by movements in prices’.68 Following Halperín Donghi, research has

tended to focus on why the expansion occurred despite falling prices.69 In the words

of one major survey, the problem became to ‘explain the paradox posited by Halperín

Donghi more than thirty years ago: the great boom in the ranching economy was

achieved during a time of declining export prices’.70 Even those, moreover, who have

correctly observed that improved terms of trade did provide price incentives for the

expansion have seriously underestimated the extent of the boom because they have

used the same type of ‘proxy’ estimates as Williamson, which have a downward bias

in the trend.71 This leads them, for instance, to see a four percent deterioration in the

terms of trade from 1820 to 1860,72 whereas the new estimates presented in Chapter

4 suggest a roughly 100 percent improvement, while they indicate that over the

course of the long nineteenth century – from the 1780s to the 1900s – they probably

improved by over 2,000 percent. Once Argentina’s terms of trade are measured more

accurately, therefore, a massive and persistent boom can be seen, so Halperín

Donghi’s paradox disappears.

Having demonstrated the magnitude of Argentina’s long terms-of-trade boom,

Chapter 4 then analyses how it reordered the River Plate, shaping the political

economy of the emerging nation. In doing so, it argues against a traditional narrative

that sees the country’s political backwardness as a remnant of a more or less distant

past. Domingo Sarmiento, Argentina’s president during 1868-74, famously expressed

the liberal form of this narrative in terms of the conflict between ‘civilisation’ and

‘barbarism’;73 Marxists would later use the terms ‘feudalism’ and ‘capitalism’;74

68. Halperín Donghi, ‘La expansión ganadera’, p. 61, author’s translation.69. The most important work to build on Halperín Donghi are H. Sabato, Agrarian Capitalism and

the World Market: Buenos Aires in the Pastoral Age, 1840-1890, Albuquerque, 1990; and S.Amaral, The Rise of Capitalism on the Pampas: The Estancias of Buenos Aires, 1785-1870,Cambridge, 1998.

70. R. Salvatore and C. Newland, ‘Between Independence and the Golden Age: The Early ArgentineEconomy’, in della Paolera and Taylor, eds., A New Economic History, p. 22.

71. See C. Newland, ‘Exports and Terms of Trade in Argentina, 1811-1870’, Bulletin of Latin Amer-ican Research, 17:3, 1998; C. Newland and J. Ortíz, ‘The Economic Consequences of ArgentineIndependence’, Cuadernos de Economía, 38:115, 2001; and Salvatore and Newland, ‘BetweenIndependence’.

72. Salvatore and Newland, ‘Between Independence’, p. 28, Table 2.1.73. D. Sarmiento, Facundo: Civilisation and Barbarism, Berkeley, (1845) 2003; also see N. Shum-

way, The Invention of Argentina, Berkeley, 1991, chs. 5-6.74. On the long debate about these categories among Latin American(ist) Marxists, see S.J. Stern,

‘Feudalism, Capitalism, and the World-System in the Perspective of Latin America and the

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modernisation theorists preferred ‘tradition’ and ‘modernity’;75 more recently, ‘neo-

institutionalists’ have revived this dualism with the contrast between good and bad

institutions, with the latter being seen as a legacy of Spanish colonialism.76 Hence, in

their discussion of Argentina Daron Acemoglu and Simon Robinson claim that the

country’s political backwardness was due to the (bad) ‘extractive’ institutions establ-

ished by the Spanish to exploit the natives in the interior’s more densely populated

regions, which negated the (good) ‘inclusive’ institutions that would later form in

Buenos Aires.77 They write:

At the time of the conquest of the Americas by the Spanish, [La Rioja, a westerninterior province,] was an outlying part of the Inca Empire and had a dense popula-tion of indigenous people. The Spanish created encomiendas here, and a highlyextractive economy developed growing food and breeding mules for the miners inPotosí to the north. In fact, La Rioja was much more like the area of Potosí in Peruand Bolivia than it was like Buenos Aires. In the nineteenth century, La Riojaproduced the famous warlord Facundo Quiroga, who ruled the area lawlessly andmarched his army on Buenos Aires. The story about the development of Argentinepolitical institutions is a story about how the interior provinces, such as La Rioja,reached agreements with Buenos Aires. These agreements were a truce: the warlordsof La Rioja agreed to leave Buenos Aires alone so that it could make money. Inreturn, the Buenos Aires elites gave up on reforming the institutions of ‘the interior’.So Argentina at best appears a world apart from Peru or Bolivia, but it is really notso different once you leave the elegant boulevards of Buenos Aires. That the prefer-ences and the politics of the interior got embedded into Argentine institutions is thereason why the country has experienced a very similar institutional path to those ofother extractive Latin American countries.78

In this latest version of the dualist analysis, then, Argentina’s political backwardness

was a result of the institutional legacies of colonialism in the interior.

The problem with the neo-institutionalist account of Argentina’s (and the

periphery as a whole’s) institutional development is that it ignores several centuries

of history.79 The principal debate among neo-institutionalists is why colonialism left

Caribbean’, American Historical Review, 93:4, 1988.75. The classic analysis is G. Germani, Política y sociedad en una epoca de transición: De la

sociedad tradicional a la sociedad de masas, 4th ed., Buenos Aires, 1971; for background, seeValenzuela and Valenzuela, ‘Modernization and Dependency’, pp. 537-43.

76. For critical overviews of this literature, see H-J. Chang, ‘Understanding the Relationship betweenInstitutions and Economic Development: Some Key Theoretical Issues’, in idem, ed., Institu-tional Change and Economic Development, New York, 2007; and L. Bértola, ‘Institutions and theHistorical Roots of Latin American Divergence’, in J.A. Ocampo and J. Ros, eds, The OxfordHandbook of Latin American Economics, Oxford, 2011, pp. 32-47.

77. D. Acemoglu and J.A. Robinson, Why Nations Fail: The Origins of Power, Prosperity, andPoverty, London, 2012, pp. 383-88.

78. Ibid., pp. 386-87.79. Cf. G. Austin, ‘The ‘Reversal of Fortune’ Thesis and the Compression of History: Perspectives

from African and Comparative Economic History’, Journal of International Development, 20:8,

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some countries with good, and other countries with bad, institutions, with particular

attention given to the contrasts between Anglo and Spanish America. Some neo-insti-

tutionalists believe that institutional differences resulted from the nature of the colon-

ies’ mother countries in Europe;80 others, like Acemoglu and Robinson, argue that the

differences evolved in response to the resources and environmental conditions that

colonists found when they arrived.81 What all tend to underplay is everything that has

happened since the colonial era, as if institutions had been fixed for all time. In this,

they repeat the mistake of previous dualist literatures, which, in the words of Andre

Gunder Frank, ignored how ‘the contemporary underdeveloped institutions of the so-

called backward or feudal domestic areas of an underdeveloped country are no less

the product of the single historical process of capitalist development than are the so-

called capitalist institutions of the supposedly more progressive areas’.82 While the

vocabulary has changed, including in Frank’s later works,83 the basic problem with

dualist theories remain, as the neo-institutionalists seek to project the origins of back-

wardness into the distant colonial past, ignoring the ways in which it has evolved

through the process of what Frank called the ‘development of underdevelopment’.84

Following Frank’s lead, Chapter 4 traces the origins of Argentina’s political

backwardness not to the colonial era, but to its integration into global capitalism. It is

2008.80. D.C. North, W. Summerhill, and B.R. Weingast, ‘Order, Disorder and Economic Change: Latin

America Versus North America’, in B. Buenos de Mesquita and H.L. Root, eds., Governing forProsperity, New Haven, 2000.

81. S.L. Engerman and K.L. Sokoloff, ‘Factor Endowments, Institutions, and Differential Paths ofGrowth among New World Economies’, in S.H. Haber, ed., How Latin America Fell Behind:Essays in the Economic Histories of Brazil and Mexico, 1800-1914, Stanford, 1997; and idem,Economic Development; D. Acemoglu, S. Johnson, and J.A. Robinson, ‘The Colonial Origins ofComparative Development: An Empirical Investigation’, American Economic Review, 91:5,2001; idem., ‘Reversal of Fortune: Geography and Institutions in the Making of the ModernWorld Income Distribution’, Quarterly Journal of Economics, 117:4, 2002; idem., ‘The Rise ofEurope: Atlantic Trade, Institutional Change, and Economic Growth’, American EconomicReview, 95:3, 2005; and Acemoglu and Robinson, Why Nations Fail, esp. Ch. 1.

82. A.G. Frank, Latin America: Underdevelopment or Revolution: Essays on the Development ofUnderdevelopment and the Immediate Enemy, New York, 1969, p. 5.

83. On Frank’s struggles with the term ‘capitalism’, see A.G. Frank, ‘Transitional Ideological Modes:Feudalism, Capitalism, Socialism’, in idem and B.K. Gills, eds., The World System: FiveHundred Years or Five Thousand?, London, 1993.

84. Frank, Latin America, ch. 1. Frank’s critique of the dualist literature has been somewhat revivedby J.H. Coatsworth, ‘Structures, Endowments, and Institutions in the Economic History of LatinAmerica’, Latin American Research Review, 40:3, 2005, esp. pp. 135-36, 139-40; also see idem,‘Inequality, Institutions and Economic Growth in Latin America’, Journal of Latin AmericanStudies, 40:3, 2008. Some of the key evidence that Coatsworth musters against the neo-institu-tionalists, his GDP per capita statistics, is, however, extremely dubious, as will be shown forArgentina in Appendix 1.1, page 53.

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contended that within Argentina the long boom allowed land-abundant regions to

prosper, even as it brought stagnation to the interior regions, which were relatively

land-scarce and/or landlocked.85 It is, then, essential to take into account the uneven

impacts of improved terms of trade on Argentina’s different regions, as they shaped

not only the famous ‘European Argentina’ that centred on Buenos Aires, but also the

‘other Argentina’ that surrounded it.86 This unevenness was central to Argentina’s

development, Chapter 4 argues, because the state was substantially built by the inter-

ior’s ruling classes, who sought a strong federal government to buttress themselves

against the discontent of their peasantries, who were losing out from the long boom.

The possibilities for the kind of white-egalitarian democracy that was being pion-

eered in the prosperous European offshoots were thus limited in Argentina because it

lacked the social consensus that facilitated democratisation in those countries. Pace

the neo-institutionalist focus on the colonial era, therefore, Chapter 4 identifies the

country’s integration into the global(ising) capitalist order as generating institutional

backwardness because the losers from the long boom – the interior’s peasantries –

had to be excluded from politics.

In making this analysis, Chapter 4 builds on Miron Burgin’s classic account

of why a unified state was unable to form in Argentina during the first half of the

nineteenth century.87 Burgin claimed that improved terms of trade drove the civil

conflicts that followed independence. ‘There was’, Burgin wrote, ‘a considerable

decrease in import prices and a simultaneous appreciation in the value of commodit-

ies destined for overseas markets’. This triggered a great expansion in exports

because ‘[f]or the first time the country was in a position to make full and open use

of the vast cattle resources which had accumulated in the past two centuries’ since

Europeans first introduced livestock to the region.88 Yet, Burgin observed, this expan-

85. It is impossible to adequately quantify exactly how land-scarce the interior was without furtherstudies of Argentina’s regional land resources and better estimates of historical populations. Atthe beginning of the long nineteenth century the North and West probably had similar land-labourratios as Bolivia and other Andean countries, which, while more land-abundant than most ofEurasia, were far less land-abundant than Australasia, North America, or, indeed, Argentina’sPampean zone.

86. The classic analysis of this fan-like structure is in A. Bunge, Una nueva Argentina, Madrid,(1940) 1984, ch. 10. The most complete account of Argentina’s interior in the twentieth centuryis L. Sawers, The Other Argentina: The Interior and National Development, Oxford, 1996.

87. M. Burgin, The Economic Aspects of Argentine Federalism 1820-1852, Cambridge, MA, 1946,esp. ch. 1.

88. Burgin, Economic Aspects, p. 11.

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sion was overwhelmingly confined to the Littoral region due to the high costs of

internal transportation from the landlocked interior to the coast, which prevented the

interior’s goods from being exported overseas. Furthermore, a ‘flood of [imported]

commodities [...] soon swamped the country’; textiles, in particular, were much

cheaper to transport overland, so they could compete with the interior’s cottage

industry, which was soon ‘faced with ruin’.89 Federalists in the interior as a result

insisted on a loose confederation of the River Plate provinces, in order to ‘protect

their industries and agriculture against the encroachments from abroad’ through

‘special tariffs, transit duties, differential taxation, and direct economic legislation’,90

all of which would have been difficult within a unified state.91

Chapter 4 builds on Burgin’s analysis by examining the formation of a

unified Argentine state in the second half of the nineteenth century, after Burgin’s

narrative ends. The key event that facilitated state formation, it argues, was the

outward turn in what Peter Cain and Anthony Hopkins have called Britain’s ‘gentle-

manly capitalism’.92 When British arable farming was undermined by the increased

supply of grain from the European offshoots, the British landed gentry responded by

fusing with the financial sector of the City of London, giving rise to a new class of

‘gentlemanly investors’ who focused on financing infrastructure projects abroad. The

89. Ibid., p. 16.90. Ibid., pp. 16-17, also pp. 134-36.91. Subsequent research on the effects of trade liberalisation on the interior’s industry has added

nuance to this picture, but without fundamentally altering it. Hence, it has been found that thecottage industries survived until the second half of the nineteenth century, but in a diminishedform, which is largely in line with Burgin’s analysis. See T. Halperín Donghi, Politics, Econom-ics and Society in Argentina in the Revolutionary Period, Cambridge, 1975, pp. 89-91; C.S.Assadourian, El sistema de la economía colonial: Mercado interno, regiones y espacio econ-ómico, Lima, 1982, pp. 253-65; J.C. Garavaglia and C. Wentzel, ‘Un nuevo aporte a la historiadel textil colonial: Los ponchos frente al mercado porteño, 1750-1850’, Anuario IEHS, 4, 1989;S. Palomeque, ‘Los esteros de Santiago: Acceso a los recursos y participación mercantil: Santi-ago del Estero en la primera mitad del siglo XIX’, Data: Revista del Instituto de Estudios Andi-nos y Amazónicos, 2, 1992, pp. 40-43; S. Romano, Economía, sociedad y poder en Córdoba:Primera mitad del siglo XIX, Córdoba, 2002, pp. 123-26, 162-65; and, for a useful overview, M.Llorca-Jaña, The British Textile Trade in South America in the Nineteenth Century, Cambridge,2012, pp. 257-70. For a recent attempt to assess the divergence between the Littoral and the inter-ior after independence, see J. Gelman and D. Santilli, ‘Crecimiento económico, divergenciaregional y distribución de la riqueza: Córdoba y Buenos Aires después de la independencia’,Latin American Research Review, 45:1, 2010.

92. P.J. Cain and A.G. Hopkins, British Imperialism 1688-2000, 2nd ed., Harlow, 2002, esp. chs 1-3.For the debates that this work has inspired, see A. Webster, The Debate on the Rise of BritishImperialism, Manchester, 2006, ch. 7. It should be stressed that Cain and Hopkins’ analysis ofBritish imperialism is in many ways a vindication and update of J.A. Hobson, Imperialism: AStudy, New York, 1902.

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land-abundant countries received the bulk of British capital exports because they

required railways to expand their frontiers, and, more importantly, they could service

substantial foreign investments due to their booming export sectors. In Argentina a

British-financed railway network then augmented the national army’s capacity to put

down rebellions in the provinces, while the railways also gave the provincial ruling

classes the opportunity to profit from the long boom for the first time, as drastically

reduced internal transportation costs meant they could send their agricultural

products to the Littoral, either for export or domestic consumption. For this reason,

the interests of the ruling classes of the Littoral and the interior began to converge,

eventually leading to a considerable integration between the two in terms of their

family and social networks.93

From this perspective, then, state formation in Argentina was a highly

conflictual process that was contingent upon developments in the North Atlantic

core. It was not, as Oscar Oszlak implied in a highly influential study, a case of a

Leviathan inevitably expanding outward from Buenos Aires.94 Rather, the state was

as much pulled into the interior as it was pushed out from the Littoral. In making this

argument, Chapter 4 draws on Ariel de la Fuente’s study of La Rioja Province, in

which he found that establishing a strong federal government appealed to those

elements of the provincial ruling classes that had traditionally depended upon the

support of the Spanish authorities, whereas Federalist strongmen (caudillos), such as

Facundo Quiroga, became prominent after independence because they could draw on

the support of the rural poor. As de la Fuente puts it:

The limitations of the provincial state selectively impacted different sectors of thelocal elite, and hence, affected their political affiliations. A federal system ofgovernment that assured the political autonomy of the province was the best altern-ative for the caudillos, who thanks to their ability to mobilize clients, had the capa-city to practice politics at the local level. But other sectors of the elite withoutcliental – and so, little opportunity to compete for political power at the local level –

93. The crucial role of the railways in this process has been identified by W. Ansaldi, ‘Notas sobre laformación de la burguesía argentina, 1780-1880’, in E. Florescano, ed., Origenes y desarrollo dela burguesía en América Latina, 1700-1955, México, 1985, pp. 550-52. The most importantstudy of the subsequent changes in the interior’s ruling classes remains J. Balán, ‘Una cuestiónregional en la Argentina: Burguesías provinciales y el mercado nacional en el desarrollo agroex-portador’, Desarrollo Económico, 18:69, 1978. For a synthesis of the subsequent literature, seeL. Losada, Historia de la élites en la Argentina: Desde la Conquista hasta el surgimiento delperonismo, Buenos Aires, 2009, pp. 146-52.

94. O. Oszlak, La formación del estado argentino: Orden, progreso y organización nacional, BuenosAires, 1997, esp. pp. 272-75.

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were in favor of a centralized system with a strong state presence at the local level.When seen from the interior of the country, the centralization of power was not onlya consequence of the policies implemented by the national state; it was also activelysought by certain sectors of the provincial elites. In the conflict between Unitariansand Federalists, then, two political projects were contested, with important ramifica-tions for different sectors of the provincial elites. And it was the weakness of theprovincial state apparatus (and initially, the national one as well) that gave thelower classes a decisive role in the political struggle, forcing the elites to cultivate acliental.95

This, then, is starkly different to the liberal interpretation of Argentina’s political

development, which, as seen above, has viewed the Federalist strongmen as relics of

Spanish colonialism. According to de la Fuente’s findings, they were in fact a reflec-

tion of the at least partial democratisation that had occurred after independence,

whereas a unified state appealed precisely to those elements of the provincial ruling

classes that had little popular support, which made it necessary for them to turn to

some external force, such as the federal government. It was for this reason that the

state was substantially built under the hegemony of the PAN, an alliance of repres-

entatives of the provincial ruling classes, as they sought a stronger federal govern-

ment that would allow them to reconquer the societies that they had ruled over

during the colonial era. That reconquest could only occur, however, once British

capital had begun to finance the infrastructure that the federal government required

to exercise its authority across its territory. Argentina’s political backwardness – that

is, its oligarchic state – thus came from its integration into global capitalism.

In making this analysis, Chapter 4 presents a far less charitable interpretation

of the PAN than has appeared in much of the recent literature. Some have interpreted

the PAN’s promotion of railways in the interior as representing a kind of develop-

mentalism for Argentina’s most backwards regions.96 Here, on the other hand, it is

maintained that the railways were principally used to reconquer the interior’s peasant

societies, at the same time as they permitted the provincial ruling classes to profit

from the long boom. What is more, the chapter shows how the material bases of

95. A. de la Fuente, Children of Facundo: Caudillo and Gaucho Insurgency During the ArgentineState-Formation Process (La Rioja, 1853-1870), Durham, NC, 2000, p. 188, emphasis added.

96. L. Llach, ‘The Wealth of the Provinces: The Rise and Fall of the Interior in the PoliticalEconomy of Argentina, 1880-1910’, PhD diss., Harvard University, 2007; and P. Gerchunoff, F.Rocchi, and G. Rossi, Desorden y progreso: Las crisis económicas argentinas, 1870-1905,Buenos Aires, 2008, chs. 1-2. Much of the inspiration for this literature can be found in T.Duncan, ‘La política fiscal durante el gobierno de Juárez Celman, 1886-1890: Una audazestrategia’, Desarrollo Económico, 23:89, 1983.

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these peasant societies were undermined by the railways because reduced costs of

internal transportation meant that cottage textile production was displaced by impor-

ted yarn and cloth. Ferrer recognised this some time ago:

Although the formation of a national market created development possibilities incertain provinces in lines of production oriented toward that market, it meant thefinal subordination of the interior. The railroads, which speeded up communicationand ended the isolation of many regions of Argentina, were the crucial factor. From1857 to 1914, the railroad grid lengthened from 10 kilometers to 33,500 kilometers.Except for Patagonia, all the interior provinces were connected by railroad withBuenos Aires and the Litoral ports. For the first time in Argentina's history,geographical distance ceased to protect the various economic regions. Imports easilyreached the interior, and their competition dealt a death blow to the shaky localindustries. For example, the production of cloth succumbed completely to importedtextiles.97

Chapter 4 reinforces Ferrer’s vision with the numbers that were often lacking in his

own account – as one critic incredulously noted, ‘Ferrer managed to write an econ-

omic history of Argentina without including a single statistical table’.98 Census data

on occupations are used to demonstrate just how substantial deindustrialisation was,

with a dramatic decline in textile employment clearly shown. The new industries that

did emerge, moreover, did not provide sufficient employment to compensate for the

loss of the cottage industries, while access to the land was limited by the highly

concentrated pattern of landownership, combined with the racism that prevented the

interior’s largely mixed-race population from becoming tenants in the Pampean zone.

Increasing underemployment then resulted from the saturation of the interior’s labour

markets, putting downward pressure on wages.

Argentina’s oligarchic state would also leave its mark on the development of

the country’s land-abundant regions. As Miguel Angel Cárcano described in his clas-

sic study, under the PAN public lands were privatised in a way that encouraged the

concentration of landownership.99 Carmen Sesto’s subsequent research then revealed

the extent to which members of the PAN used laws that were ostensibly designed to

redistribute land to actually appropriate it themselves.100 Hilda Sabato’s data for

97. Ferrer, Argentine Economy, p. 129.98. Haber, ‘Introduction: Economic Growth’, p. 8.99. M.A. Cárcano, Evolución histórica del régimen de la tierra pública 1810-1916, 3rd ed., Buenos

Aires, 1972. 100. C. Sesto, ‘Implementación de la política estatal ganadera en la Provincia de Buenos Aires’,

Investigaciones y Ensayos, 32, 1982.

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Buenos Aires, which are used in Chapter 4, indicate that landownership accordingly

became more concentrated,101 despite optimists’ claims to the contrary.102 Restricted

access to the land then made it difficult to become a smallholder, while immigrants

also found it more difficult to become tenants as their numbers swelled.103 As Ferrer

again recognised, this meant that the frontier did not act as a safety valve for labour

markets:

With no farmland available, the immigrant was obliged to work as a tenant farmeror as a field hand and to accept low wages. The profits, interests, and rent generatedby rural output were concentrated in the hands of a small proportion of thepopulation. [...]

Furthermore, land concentration also affected the remuneration of labor inurban activities: first, by swelling the supply of manpower for urban employment,which kept wages down; and second, by establishing poor pay for alternative activ-ities in agriculture. The pressure of cheap manpower in urban centers was reflectedin the large ratio of unemployment. [...] Thus, land concentration was the decisivefactor in the level of remuneration of labor in agricultural and urban activities and inthe share of labor in net income.104

Land concentration in this way made Argentina deviate from a European offshoot-

style development path by muting the safety-valve effect of the frontier, which

reduced the incentives for the kind of mechanised intensive growth that was taking

place in the United States.

According to the analysis made in Chapter 4, it was, then, the lack of a white-

egalitarian democracy that prevented Argentina’s land resources from being as effect-

ively used as in the European offshoots. This was because land abundance was, to a

degree, ‘socially constructed’,105 as people had to be given easy access to the land for

the expanding frontier to have its safety-valve effect on labour markets. In the

European offshoots access was given through a variety of white-egalitarian policies,

such as the US Homestead Acts, which provided free public land for settlers.106 In

101. Sabato, Agrarian Capitalism, ch. 2102. Most importantly, A.M. Taylor, ‘Latifundia as Malefactor in Economic Development? Scale,

Tenancy, and Agriculture on the Pampas, 1880–1914’, Research in Economic History, 17, 1997,pp. 274-78.

103. See J. Adelman, Frontier Development: Land, Labour, and Capital on the Wheatlands of Argen-tina and Canada, 1890-1914, Oxford, 1994, ch. 4.

104. Ferrer, Argentine Economy, p. 116.105. Cf. A.P. David and G. Wright, ‘Increasing Returns and the Genesis of American Resource

Abundance’, Industrial and Corporate Change, 6:2, 1997; also G. Wright and J. Czelusta, ‘WhyEconomies Slow: The Myth of the Resource Curse’, Challenge, 47:2, 2004.

106. For a description of this and the various other ways in which settlers accessed the land in theEuropean offshoots, see J.C. Weaver, Great Land Rush and the Making of the Modern World,

- 36 -

Argentina, on the other hand, such policies proved far more difficult to implement

due to its political backwardness. As a result, Argentina became a land abundant

country with widespread landlessness, as the ‘floating population’ of landless day

labourers grew: by the First World War it accounted for around 40 percent of the

male working population outside of the capital city.107 This mass of unskilled workers

saturated labour markets, leading to underemployment, which put downward pres-

sure on wages. Consequently, capitalists had fewer incentives to invest in machinery

and equipment, so intensive growth was limited.108 Hence, Chapter 4 concludes, the

institutional legacies of Argentina’s integration into global capitalism prevented it

from fulfilling its potential as a land-abundant country.

The Development GapTo test this pessimistic revision, Chapter 5 evaluates the common claim that Argen-

tina began the twentieth century as ‘one of the richest countries in the world’. The

chapter adopts a comparative methodology, as living standards in Argentina prior to

the First World War are compared with those of various countries in Northern

Europe, its land-abundant offshoots, Southern Europe, and South America. To do so,

the chapter looks at ‘human development’ as a ‘process of enlarging people’s

choices’, particularly their capacity to ‘lead a long and healthy life, to be educated

and to enjoy a decent standard of living’, including ‘political freedom’.109 Unlike in

other studies that have adopted this approach to living standards, Chapter 5 does not

calculate Human Development Indices (HDIs).110 Instead, it offers a more considered

1650-1900, Montreal, 2003, chs. 4-7.107. The term ‘floating population’ was used by contemporaries. See, for example, A.E. Bunge,

Riqueza y renta de la Argentina: Su distribución y su capacidad contributiva, Buenos Aires,1917, p. 278. The most valuable account of this part of the labour force in the Pampean zoneremains C. Solberg, ‘Farm Workers and the Myth of Export-Led Development in Argentina’,Americas, 31:2, 1974; also see J. Adelman, ‘The Harvest Hand: Wage-Labouring on the Pampas,1890-1914’, in idem, ed., Essays in Argentine Labour History, 1870-1930, London, 1992; andidem, Frontier Development, pp. 116-30. For the North and West, see J. Balán, ‘Migraciones,mano de obra y formación de un proletariado rural en Tucumán, Argentina, 1870-1914’, Demo-grafía y Economía, 10:2, 1976; D.J. Guy, ‘The Rural Working Class in Nineteenth-CenturyArgentina: Forced Plantation Labor in Tucumán’, Latin American Research Review, 13:1, 1978;and R.D. Salvatore, ‘Labor Control and Discrimination: The Contratista System in Mendoza,Argentina, 1880-1920’, Agricultural History, 60:3, 1986.

108. Again, see Adelman, Frontier Development, ch. 7.109. UNDP, Human Development Report, New York, 1990, p. 10.110. N.F.R. Crafts, ‘The Human Development Index and Changes in Standards of Living: Some

Historical Comparisons’, European Review of Economic History, 1:3, 1997; idem, ‘The HumanDevelopment Index, 1870-1999’, European Review of Economic History, 6:3, 2002; P. Astorga,

- 37 -

assessment of indicators of political institutions, public welfare, and the purchasing

power of wages, which is a measure of incomes that is more reliable than the histor-

ical GDP statistics that other studies use.111

The indicators examined in Chapter 5 do not place Argentina among the

world’s most developed countries. Argentina’s political institutions lagged far behind

Britain and the European offshoots; in terms of health and education, Argentina was

at roughly Southern European levels; and workers' incomes were higher than in Italy

or Spain but below the levels of Northern Europe, let alone the European offshoots.

Such comparisons hardly suggest, therefore, that Argentina was one of the world’s

most developed countries. Indeed, precisely for this reason, even those studies that

have incorporated dubious GDP statistics into their HDIs have not been kind to

Argentina. Nicholas Crafts, for instance, assigned Argentina a HDI in 1913 of 0.51,

which was somewhat better than Italy (0.49) and Spain (0.42), but considerably

below France and Germany (both 0.61), or Britain and the United States (both

0.64).112 The conclusions of Chapter 5 should not, then, be entirely surprising, even if

the optimists have been slow to absorb the findings of the HDI literature.

In explaining these results, Chapter 5 builds on the analysis presented in the

previous chapter, focusing especially on the backwardness of Argentina’s political

institutions. It follows David Rock, who has shown that the system established by the

PAN in the 1870s persisted until the early twentieth century.113 Rock and his co-

author Fernando López-Alves neatly summarise what the system consisted of:

In the prosperous late 1860s and the early 1870s patronage ties replaced coercion asthe chief method of maintaining the control of the national government over theprovinces. [...] As the conduits of such patronage from the national government, theprovincial governors emerged as critical components of the political system and theoffice of governor became the object of intense competition. [...] A successfulcandidate for governor needed to win the support of the military commandersstationed in the region, the provincial legislatures and the jueces de paz [magis-trates], who controlled elections at the county or municipal level. Once installed inpower, governors commonly appointed members of their own families to seniorprovincial offices and stacked the legislatures with their followers. Such conditionsbecame more pronounced as time passed, particularly in the more undevelopedprovinces. [...] When their terms ended, the governors often sought election to the

A.R. Berges, and V. Fitzgerald, ‘The Standard of Living in Latin America During the TwentiethCentury’, Economic History Review, 58:4, 2005; and L. Prados de la Escosura, ‘ImprovingHuman Development: A Long-Run View’, Journal of Economic Surveys, 24:5, 2010.

111. Again, see Appendix 1.1 for the problem with historical GDP statistics.112. Crafts, ‘Human Development Index, 1870-1999’, p. 396, Table 2.113. D. Rock, State Building and Political Movements in Argentina, 1860-1916, Stanford, 2002.

- 38 -

national senate, a body later sarcastically described as ‘a haven of rest dedicated toex-Governors of Provinces’. [... P]rovincial office-holding became a means to amasslanded property. It provided a means to influence the choice of railway routes, andin the arid north and west to use irrigation works as instruments of patronage andpolitical pressure.114

In much of the country this system remained intact until (at least) the First World

War, with only the more developed areas, especially the urban centres, having a more

democratic politics, associated particularly with the Radical Civic Union (UCR).115

Hence, in Paula Alonso’s words:

The UCR was the first national party with a permanent party structure solelysustained by the private resources of its leaders and from public appeals andcampaigns. This was only made possible by the existence of a more affluent societywhose members could invest in party organization and whose followers could buyand read newspapers and contribute to the campaigns. It cannot be a coincidencethat the party’s main strongholds were located in the more developed areas of thecountry, such as the city and Province of Buenos Aires, south of Santa Fe, Córdoba,and Mendoza, areas with higher literacy rates, greater affluence and denserpopulations.116

The PAN’s rule can, from the perspective of Chapter 5, be seen as both perpetuating

and being perpetuated by Argentina’s uneven development, as the low levels of

human development that afflicted much of the country, especially low literacy rates

and low incomes, prevented democratisation, thus allowing the PAN to maintain its

rule, which in turn prevented Argentina from becoming one of the world’s most

developed countries by restricting access to its substantial land resources.

Numbers, Myths, MetanarrativesIn summary, then, the pessimistic revision of Argentina’s long nineteenth century is

based on the new metanarrative developed in the first half of this dissertation.

Chapter 2 argues that some of the issues raised in Williamson’s recent work on the

114. F. López-Alves and D. Rock, ‘State-Building and Political Systems in Nineteenth-CenturyArgentina and Uruguay’, Past & Present, 167, 2000, pp. 192-93.

115. Also see E. Gallo and S. Sigal, ‘La formación de los partidos políticos contemporáneos: LaUnión Cívica Radical (1890-1916)’, Desarrollo Económico, 3:1-2, 1963, pp. 212-22; D. Rock,Politics in Argentina 1890-1930: The Rise and Fall of Radicalism, Cambridge, 1973, chs. 1-3.; P.Alonso, Between Revolution and the Ballot Box: The Origins of the Argentine Radical Party inthe 1890s, Cambridge, 2000, pp. 11, 159-60; and M. Bonaudo, ‘Society and Politics: From SocialMobilization to Civic Participation (Santa Fe, 1890-1909)’, in J.P. Brennan and O. Pianetto, eds.,Region and Nation: Politics, Economics, and Society in Twentieth Century Argentina, New York,2000.

116. Alonso, Between Revolution, p. 11.

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periphery’s terms-of-trade boom are important, but he has undermined his own case

by relying upon dubious data. Were better data used, the periphery’s boom would

appear much longer, of greater magnitude, and more widespread than Williamson

supposes. Chapter 3 then goes beyond Williamson by outlining an alternative

metanarrative of how this long boom drove global divergence. It contends that the

terms-of-trade boom increased global inequality due to its effects on the labour

market: in the land-abundant European offshoots it allowed frontiers to expand,

which prevented labour markets from becoming saturated, while in the land-scarce

periphery deindustrialisation depressed wages because of the diminishing returns that

came from applying a greater amount of labour to a more or less fixed supply of

land. In this way, the dissertation analyses how global capitalism generated what

Frank called the ‘development of underdevelopment’ through the terms of trade.

The second half of the dissertation then applies this new metanarrative to the

case of Argentina. It begins in Chapter 4 with an overview of how a massive terms-

of-trade boom reordered the River Plate, shaping Argentina as an emerging nation.

The chapter discusses first how the long boom generated disorder due to its uneven

impacts on land-scarce and land-abundant regions, then how a new order was establ-

ished in the second half of the nineteenth century thanks to massive inflows of Brit-

ish investment. The new state would, Chapter 4 argues, be an oligarchic state because

the losers from the long boom had to be excluded from politics. Political backward-

ness then prevented Argentina’s from realising its potential, particularly by ensuring

that landownership remained highly concentrated. Chapter 5 reinforces that conclu-

sion by comparing living standards in Argentina with those in Europe, its offshoots,

and South America. It finds that whether measured in terms of political institutions,

public welfare, or national income, Argentina was not among the most developed

countries in the world. Consequently, as discussed further in Chapter 6, the conclu-

sion of this dissertation, the starting point of the Argentine morality tale – its ‘once

upon a time’ – is wrong. There is, in other words, no Argentine paradox because the

optimistic vision of its ‘golden age’ is a myth.

Appendix 1.1: Argentina’s GDP, 1800-2012This appendix discusses why Argentina’s GDP statistics should not be considered

- 40 -

reliable, and why, for this reason, they will not be used in this dissertation. The

appendix begins by discussing the problems with the official GDP statistics during

the period 1935-2012, then goes on to outline the problems with the unofficial estim-

ates covering 1800-1935. To understand why this long timespan has been adopted, it

is necessary to take into account the way in which historical GDP statistics are

constructed. In short, the most common method is to extrapolate back from a more or

less recent purchasing-power-parity (PPP) benchmark estimate using volume indices

of historical GDP.117 The problems with twentieth-century GDP statistics matter to

historians of the nineteenth century, then, because they provide the volume indices

that are used to estimate nineteenth-century GDP levels, which means that any error

in the statistics for the twentieth century will also affect the estimate of nineteenth-

century GDP levels. This appendix is therefore intended to contribute to the growing

awareness of the problems in the standard methods used to produce historical GDP

statistics.118

The Official Estimates, 1935-2012The first official (that is, government-produced) estimates of Argentina’s GDP were

made by the Central Bank in 1946; they covered the period 1935-45, with 1935 used

as their base year. Subsequently, various other estimates would be made, with various

base years. Initially they were calculated from census data on the value of output,

with price series used to deflate nominal values into ‘constant’ base-year prices.

Interpolations between, and extrapolations from, census-year data then occurred

using volume indices constructed from data on output and employment. The result-

ing ‘constant’ price GDP series were then reflated using price indices to give series in

‘current’ prices. Thereafter, the methodology used appears to have shifted away from

117. See, for example, A. Maddison, The World Economy, II, Historical Statistics, Paris, 2006. Thismethodology will be further discussed in Chapter 5, pages 208-10.

118. See M. Jerven, ‘An Unlevel Playing Field: National Income Estimates and Reciprocal Compar-ison in Global Economic History’, Journal of Global History, 7:1, 2012; also K. Fukao, D. Ma,and T. Yuan, ‘Real GDP in Pre-War East Asia: A 1934-36 Benchmark Purchasing Power ParityComparison with the US’, Review of Income and Wealth, 53:3, 2007. For examples of how somehistorians have carried on regardless of the problems with their methodology, see J. Bolt and J.Luiten van Zanden, ‘The First Update of the Maddison Project: Re-Estimating Growth Before1820’, Maddison-Project Working Paper 4, Groningen Growth and Development Centre, 2013,online at http://www.ggdc.net/maddison/maddison-project/abstract.htm?id=4 (accessed 6November 2013); and S. Broadberry, ‘Accounting for the Great Divergence’, Working Paper 184,Economic History Department, London School of Economics, 2013, online at http://eprints.lse.ac.uk/54573/(accessed 11 December 2013).

- 41 -

census data toward using just the volume indices.119

Laura Randall’s early discussion of the problem of ‘lies, damn lies, and

Argentine GDP’ highlighted the index-number problem in the official estimates.120

Randall found that five different manufacturing-output indices showed annual trend

growth rates ranging from 2.1 percent to 6.1 percent for the period 1943-55,121 with

the differences between them principally due to the choice of base year. From this,

she concluded that there was a high degree of arbitrariness in the GDP series

commonly used by historians, so the conclusions drawn from them should be

considered doubtful. Unfortunately, Randall’s warning not to trust Argentine GDP

statistics was widely ignored, not least in her own work.122

Even more important than the index-number problem highlighted by Randall,

however, is that of coverage. In short, Argentine government statisticians have lacked

much of the data that would have been necessary to accurately measure production,

particularly in the earlier estimates. The result was a major downward bias in the

trend of GDP because it tended to be the newest, fastest growing sectors for which

data were lacking. Juan Sourrouille described this problem in his history of Argen-

tina’s national accounts:

It is clear [...] that the most reliable data are for censal years and for those sectors forwhich current production statistics or accounting data are available. Intercensalinterpolations for these sectors are especially subject to increasing error over timebecause they include most of those activities which have been growing and chan-ging most rapidly in Argentina. Each subsequent census has in fact revealed thatinterpolations of gross product for these sectors have had a systematic downwardbias. The most dramatic example of such bias is the series on industrial grossproduct published prior to the revision of 1964. This series was interpolated usingthe old index of industrial production constructed from the census of 1943, in whichthe industries that developed rapidly after World War I1 were very inadequatelyrepresented. When the results of the 1953 census became available, it was thereforefound that the value of industrial production was 53 percent higher than nationalaccounts estimates. This downward bias appears to have been greatly reduced inlater interpolations of manufacturing gross product, for example, the differencebetween the estimate for 1963 and that contained in the census for this year being

119. On the history of Argentina’s national accounts, see BCRA, Sistema de cuentas del producto eingreso de la Argentina, III, Series históricas de cuentas nacionales de la Argentina, BuenosAires, 1976; J.V. Sourrouille, ‘The Development of National Accounts in Argentina’, Review ofIncome and Wealth, 22:4, 1976; ECLA, ‘Estadísticas de corto plazo de la Argentina’, I, ‘Cuentasnacionales, industria manufacturera y sector agropecuario pampeano’, Documento de Trabajo 28,ECLA Buenos Aires, 1988, pp. 33-141; and R.G. Martínez, ‘Recopilación de series históricas delproducto y del ingreso’, LC/BUE/R.242, ECLA Buenos Aires, 1999, pp. 6-13.

120. Randall, ‘Lies, Damn Lies’.121. Calculated from ibid., p. 143.122. See L. Randall, An Economic History of Argentina in the Twentieth Century, New York, 1978.

- 42 -

about 7 percent. Differences between national accounts estimates and 1963 censusdata were, however, greater for the trade and services sectors, because estimates forthese sectors are partially based on extrapolations of the labor force, which duringthe 1950s did not adequately reflect the changes that took place in the relationbetween output and employment.123

More problematic still was the lack of coverage of the informal sector, which

did not feature in the censuses, and was only incorporated into the national accounts

in the 1990s. For historians, this matters because the informal sector grew faster than

the formal sector, thereby introducing a downward bias in the trend of the GDP

volume indices that are typically used to estimate historical GDP statistics.

Consequently, past GDP levels have been overestimated. This can be illustrated by

Adrían Guissarri’s application to Argentina of a commonly used methodology to

estimate the output of the informal sector. He finds that it grew at an annual trend

rate of 5.9 percent during 1930-85, while the formal sector (that is, the unadjusted

official GDP estimate) grew by three percent; combined, they show that the overall

GDP growth rate was 3.6 percent.124 The absence of the informal sector thus means

that the official statistics underestimate growth. Consequently, when they are used to

extrapolate backwards from recent benchmarks they will overestimate past GDP

levels. In Figure A1.1 this can be seen, as the official GDP statistics and Guissarri’s

adjusted series have been used to extrapolate back from Angus Maddison’s bench-

mark level for 1980, with both series shown as percentages of US GDP per capita.

For the thick line, extrapolation was done using the official estimate, whereas for the

thin line, Guissarri’s adjusted series was used. The difference between them is

impressive: the unadjusted series suggests that Argentina’s GDP per capita was 60

percent of US GDP per capita in 1930, and that the country then experienced steady

123. Sourrouille, ‘Development of National Accounts’, pp. 355-56.124. A. Guissarri, La Argentina informal: Realidad de la vida económica, Buenos Aires, 1989, ch. 4,

Cuadro 13, available online at http://www.hacer.org/pdf/Arginfo.pdf (accessed 12 November2013); also see idem, ‘La demanda de circulante y la informalidad en la Argentina: 1930-1983’,Cuadernos de economía, 24:72, 1987. The methodology used by Guissari to estimate the size ofthe informal sector was developed by V. Tanzi, ‘The Underground Economy in the United States:Annual Estimates, 1930-80’, International Monetary Fund Staff Papers, 30:2, 1983. It is basedon the assumption that there is a normal demand for money that is determined by formal activity,the interest rate, and inflation. Regressions are then used to calculate how far the money supply isbeyond the level of demand suggested by those indicators, which is then taken as a sign ofinformal activity. Guissarri also provides an estimate based on electricity usage, which provides asimilar result to the monetary method. Guissarri, Argentina informal, ch. 4, Cuadro 17. Note thatGuissarri extended the official GDP estimate back from 1935 to 1930 using one of the unofficialextensions discussed below.

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Figure A1.1Argentina’s Relative GDP Per Capita, 1930-85

0

10

20

30

40

50

60

70

80

90

1920 1930 1940 1950 1960 1970 1980 1990

60

39 37

USA = 100

Unadjusted

Adjusted Includes estimate

of Argentina's informal sector

Note: The GDP per capita of both Argentina and the United States were calculated by usingvolume indices to extrapolate from GDP per capita in international dollars in 1980.

Sources: 1980 benchmark GDPs: A. Maddison, The World Economy in the 20th Century,Paris, 1988, p. 112, Table A-1. Argentina’s formal and informal GDP: Guissarri, Argentinainformal, ch. 4, Cuadro 13. US GDP and populations: Maddison, World Economy, II, pp.460-61, 463-64, 500-01. For the GDP estimates, see Table DA.1 in the Data Appendix.

relative decline until reaching Maddison’s benchmark level of 37 percent in 1980,

which is the standard narrative found in much of Argentina’s historiography; the

adjusted series, by contrast, shows little decline, as it begins at 39 percent in 1930,

then falls to the 37 percent benchmark level in 1980. Of course, this begs the ques-

tion: How much of the country’s apparent decline – the so-called Argentine para-

dox – is simply due to a failure to take into account the growth of the informal

sector? Guissarri himself made a similar observation,125 yet his warning, like those of

Randall and Sourrouille, has generally been ignored, since historians have instead

preferred to put their faith in the statistics produced by officialdom.

The Unofficial Extensions, 1800-1935There have been two main attempts to extend the official series back from 1935:

125. Guissarri, Argentina informal, ch. 4.

- 44 -

1) The first and most influential was made by the Economic Commission for

Latin America (ECLA), working with the cooperation of Argentina’s govern-

ment. Released in 1958, the ECLA extension provided a series for GDP in

constant 1950 prices for the period 1900-35, which was spliced with an offi-

cial estimate, then presented as if it were one series.126 The authors of this ex-

tension expressed major reservations about its quality, ‘above all for the in-

dustrial and construction sectors, which are most worrying’,127 but economists

and historians have routinely used their numbers without mentioning any

such issues. Indeed, in 1988 Gerardo della Paolera even extended the ECLA

series back to 1884 using various indirect indicators, which were, in his

words, the ‘physical volume of exports and imports; indirect trade indexes

that include: tons carried in rail roads, in ships and passengers transported in

railroads; population; gross investment figures including: public sector con-

struction, private non-agriculture construction and railroad investments’.128

This ECLA-della Paolera extension would then be reproduced, without any

methodological notes, in a widely used compilation of Argentina’s historical

statistics.129

2) In 1994 Roberto Cortés Conde provided an alternative extension covering the

period 1875-1935. His methodology consisted of measuring the physical out-

put of various sectors for as much of this period as possible, then weighting

them according to their shares of employment in 1895 and of GDP in 1914.130

In 1997 Cortés Conde released a mildly revised version of his series (without

giving any indication of how or why the revisions had been made),131 which

would also be reproduced in the same compilation of Argentina’s historical

statistics as the ECLA-della Paolera extension, again without any methodolo-

gical notes.132

126. ECLA, El desarrollo económico de la Argentina: Anexo: Algunos estudios especiales yestadísticas macroeconómicas preparadas para el informe, Santiago de Chile, 1958, Anexo 1.

127. Ibid., p. 25, author’s translation.128. G. della Paolera, ‘How the Argentine Economy Performed During the International Gold Stand-

ard: A Reexamination’, PhD diss., University of Chicago, 1988, p. 189.129. Della Paolera and Taylor, eds., A New Economic History, data CD, Series YZD.130. Cortés Conde, ‘Estimaciones del producto’.131. Cortés Conde, Economía argentina, pp. 230-31, Cuadro A1.132. Della Paolera and Taylor, eds., A New Economic History, data CD, Series YZC.

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Table A1.1Three Estimates of Argentina’s GDP Growth, 1875-1913

Annual trend growth rate, %1875

to1913

1884to

1913GDP

ECLA-della Paolera n.a. 4.9Cortés Conde 6.4 6.1Cortés Conde (rev.) 7.0 6.2

GDP per capitaECLA-della Paolera n.a. 1.5Cortés Conde 3.0 2.8Cortés Conde (rev.) 3.6 2.9

Sources:

GDP: della Paolera, ‘How the Argentine Economy’, p. 187, Table 37; Cortés Conde,‘Estimaciones del producto bruto’; and idem, Economía argentina, pp. 230-31, Cuadro A1.See Table DA.1 in the Data Appendix for the series.

Population: Z. Recchini de Lattes and A.E. Lattes, eds., La población de Argentina, BuenosAires, 1975, p. 199, Tabla 1.

As mentioned in this chapter, Cortés Conde found a considerably higher

growth rate for the late nineteenth century than had previously been supposed. Table

A1.1 shows that the revised version of his series leads to a 2.9 percent annual trend

growth rate of GDP per capita during 1884-1913, whereas the ECLA-della Paolera

series has a 1.5 percent annual growth rate. To put these numbers in perspective, the

most recent update to Angus Maddison’s widely used database contains GDP per

capita for 29 countries other than Argentina for 1884-1913.133 According to Cortés

Conde’s extension, Argentina experienced the most rapid per capita growth in the

world during this period, as its rate of 2.9 percent per year was greater than Canada,

with 2.8 percent, and than Peru, with 2.6 percent. On the other hand, according to the

ECLA-della Paolera estimate, Argentina was in fourteenth place, slightly behind

France. Cortés Conde’s extension in this way suggests spectacular per capita growth,

but the ECLA-della Paolera extension indicates a distinctly middle-of-the-road

performance. It was because of this extraordinary growth rate that the authors of the

Maddison update have recently chosen not to use Cortés Conde’s extension, prefer-

133. Bolt and Luiten van Zanden, ‘The First Update’, underlying data available online at http://www.ggdc.net/maddison/maddison-project/data/mpd_2013-01.xlsx (accessed 12 November2013).

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ring the ECLA-della Paolera series instead.134

Some of the problems with Cortés Conde’s extension can be illustrated with

his industrial output index, which is particularly important due to the role that it has

played in debates about Argentina’s industrialisation.135 In his original series Cortés

Conde showed industry growing at a phenomenal annual trend rate of 8.4 percent

during 1875-1913, which was then increased to 8.8 percent in the revised version.

Understanding how he arrived at these numbers is, however, difficult, given what he

has revealed about the components of the industrial output index. For 1875-1913, the

index appears to have been calculated from just nine underlying series that together

made up 42 percent of industrial value added in 1914.136 They were: flour, flour

products, meat products, and sugar, all from 1875 onwards; beer from 1876; textiles

from 1879; wine from 1892; dairy products from 1894; and tobacco products from

1900.137 Unfortunately, Cortés Conde did not reproduce these series, although he has

published the average annual growth rates for food and textiles, as shown in Table

A1.2. The most curious aspect of these numbers is that the industrial output index as

a whole has an extremely high growth rate for the 1890s, even though food

processing, which was by far the largest sector, grew much more slowly. Thus, food

accounted for 69 percent of the value of the index in its 1914 base year,138 and,

although Cortés Conde did not reveal the weights he used for the 1895 base year, it

seems unlikely that the share of food was substantially less. Consequently, it is

unclear in purely mathematical terms how Cortés Conde arrived at a 12 percent

growth rate for the 1890s, given that the dominant component of his index grew so

slowly.

There are two main possible explanations for the rapid industrial growth

found by Cortés Conde in the 1890s:

1) It was driven by textiles output, which apparently grew by 13 percent per

year in the 1890s. This, however, seems unlikely because Cortés Conde states

134. This is the logical implication of their statement that extrapolating back using Cortés Conde’sseries ‘casts too low a figure’ for 1875. Bolt and Luiten van Zanden, ‘First Update’, p. 20.

135. Again, see Rocchi, Chimneys in the Desert, pp. 21, 24-25, 42; and Barbero and Rocchi,‘Industry’, pp. 264-65. Also see the discussion earlier in this chapter, pages 17-18.

136. Cortés Conde, ‘Estimaciones del producto’, p. 10. 137. Ibid., pp. 13-14.138. Ibid., p. 10.

- 47 -

Table A1.2Cortés Conde’s Industrial Growth Rates for Argentina, 1875-1910

Annual growth rate, %

Total Food Textiles

1875-90 5.2 5.6 3.9

1890-1900 11.5 4.2 12.71900-10 7.8 6.7 7.4

Source: Cortés Conde, Economía argentina, pp. 207, 209, Cuadros 15 and 17.

that textiles only made up five percent of the value of his index in its 1914

base year,139 and it is improbable that he assigned it a greater value for his

1895 base year.140

2) The rapid industrial growth in the 1890s may alternatively have been driven

by the other series aggregated in Cortés Conde’s index. Given that tobacco

products were only included from 1900 onward, this leaves beer and wine –

goods that made up six and 10 percent respectively of his sample in the 1914

base year.141 Combining these weights with those given to food and textiles

suggests that beer and wine must somehow together have expanded at around

40 percent per year during 1890-1900 for the overall index to have a 12 per-

cent growth rate.

Surprisingly, this is a plausible explanation for the rapid growth found

by Cortés Conde, as can be seen by examining how he estimated the output of

these industries. For both, he states that he relied upon data from the internal

production taxes that began to be levied on certain goods at the beginning of

the 1890s.142 To understand why this methodology may have led to a roughly

40 percent annual growth rate for beverages, the available production tax data

for beer and wine are reproduced in Tables A1.3 and A1.4. They show that the

139. Ibid., pp. 10-11.140. Even if he did somehow give textiles a much greater weight, moreover, his method of calculating

textiles output is highly questionable, as it appears that he summed a (presumably) fixed percent-age of the value of dirty wool exports, the value of yarn imports, and the value of raw cottonproduction, then deflated the total by an index of imported cloth prices. Ibid., p. 14. Why dirty-wool exports should be taken as an indicator of the amount of wool being processed domesticallyis not explained, while, as was will be seen in Chapter 4, pages 168-70, the rapid growth of yarnimports is likely to have reflected the displacement of the country’s own domestically-producedyarns, so should not be taken as an indication of the amount of yarn actually being turned intocloth.

141. Ibid., p. 10.142. Ibid., p. 14.

- 48 -

beer output taxed increased at a trend rate of 10 percent per year during

1891-99, while wine output taxed grew by an incredible 64 percent per year

during 1892-1900. Wine could, therefore, explain Cortés Conde’s 12 percent

industrial growth rate during the 1890s.

If this reconstruction of Cortés Conde’s findings is correct, the prob-

lem is that in reality there was no such increase in wine output, as the 64 per-

cent growth rate merely reflected the extension of the taxes levied to ‘natural

wines’, which made up the vast bulk of production, but only began to be

taxed in 1898, when a tax of 0.04 paper pesos (m$n) per litre was imposed.143

By contrast, the land cultivated with vines, a more accurate indicator of wine

output, grew at an annual rate of roughly five percent during the 1890s.144 If

this is the explanation for Cortés Conde’s high industrial growth rate, it is,

then, the result of a fairly obvious error.

Various indirect indicators of Argentina’s industrial output also contradict

Cortés Conde’s estimate of nine percent annual growth for 1875-1913 as a whole.

Reproduced in Table A1.5, these proxies predominantly relate to the apparent supply

of raw materials and other inputs used in various industries, which have been

compiled from trade and agricultural statistics; exports are also used for some indus-

tries, with fairly crude adjustments made for domestic consumption. Together,

according to the 1914 census, the represented industries made up half of industrial

value added in 1913. Some did expand at the kind of rate suggested by Cortés

Conde: the proxies for sugar refining and metallurgy increased by nine percent annu-

ally; for flour milling and winemaking by around eight percent. Yet indicators for

other industries show far slower growth: slaughterhouse products grew at roughly

three percent per year due to the poor performance of hides, and dried and salted

meat; tobacco products and clothing expanded by possibly three percent. These

figures therefore make it extremely difficult to see how industrial output could have

grown at a trend rate of nine percent during 1875-1913. Before Cortés Conde’s

143. See P. Barrio de Villanueva, ‘Controles estatales a la industria del vino en Mendoza, 1890-1914’,H-industri@: Revista de historia de la industria, los servicios y las empresas en América Latina,4:7, 2010, pp. 8-9, available online at http://www.hindustria.com.ar/images/client_gallery/HindustriaNro7Barrio.pdf (accessed 14 May 2013).

144. DGEE, Estadística Agrícola: Año Agrícola 1913-14, Buenos Aires, 1914, p. 18.

- 49 -

Tabl

e A1

.3A

rgen

tine

Prod

uctio

n Ta

x D

ata

for B

eer,

1891

-190

0

Pro

duct

ion

taxe

d(lt

s)Ta

x ra

ised

(m$n

)

Taxe

s le

vied

(m$n

)S

ingl

eex

tract

,pe

r lt

Dou

ble

extra

ct,

per l

t

Per

bot

tle,

less

than

40 c

l

Per

bot

tle, m

ore

than

40

clC

asks

,pe

r lt

1891

7,22

0,68

026

7,85

50.

020.

0518

9210

,743

,179

267,

477

0.01

0.03

1893

11,8

87,4

3045

7,68

00.

020.

0518

9412

,477

,070

355,

341

0.01

0.03

1895

15,0

80,3

1442

7,64

80.

030.

0318

9616

,085

,334

482,

560

0.03

0.03

1897

n.a.

742,

935

0.05

0.05

1898

15,2

36,9

9076

1,84

90.

050.

0518

9919

,697

,825

928,

693

0.02

0.03

50.

0519

00n.

a.1,

155,

509

0.02

0.03

50.

05

Sour

ces:

Com

pile

dfr

omD

GEN

,Anu

ario

1896

,II,

pp.4

7-48

;ide

m,A

nuar

io18

98,I

I,pp

.73-

74;i

dem

,Anu

ario

1899

,II,

pp.2

15-2

16;i

dem

,Anu

ario

1900

,II

, pp.

285

-86;

and

Tor

nqui

st, E

cono

mic

Dev

elop

men

t, pp

. 295

, 298

-99.

- 50 -

Tabl

e A1

.4A

rgen

tine

Prod

uctio

n Ta

x D

ata

for W

ine,

189

2-19

00

Pro

duct

ion

taxe

d (lt

s)

Tax

rais

ed(m

$n)

Taxe

s le

vied

(m$n

)

Tota

lN

atur

alO

ther

sN

atur

al(p

er lt

)A

rtific

ial

(per

lt)

Ble

nded

and

petio

t(p

er lt

)

Wat

ered

or

man

ipul

ated

(per

lt)

Rai

sin

(per

lt)

Forti

fied

(per

deg

ree

exce

edin

g16

o )18

925,

597,

155

05,

597,

155

560,

433

n.a.

1893

258,

849

025

8,84

925

,885

n.a.

1894

1,23

3,58

70

1,23

3,58

712

3,35

90.

1018

9515

,250

,208

015

,250

,208

159,

502

0.10

1896

5,11

1,65

10

5,11

1,65

128

1,42

80.

120.

040.

070.

0218

97n.

a.n.

a.n.

a.95

,211

0.12

0.06

0.07

0.02

0.01

1898

49,5

24,7

2347

,815

,010

1,70

9,71

31,

906,

745

0.04

0.12

0.06

0.07

0.02

0.01

1899

122,

821,

727

121,

200,

652

1,62

1,07

53,

508,

963

0.02

0.14

0.08

0.09

0.04

1900

125,

910,

730

125,

076,

954

833,

776

3,62

4,80

50.

020.

140.

080.

090.

04

Sour

ces:

As

in T

able

A1.

3.

- 51 -

Table A1.5Evidence of Industrial Growth in Argentina, 1870s-1913

% of1913value

added*

Indicators Startyear

Annualtrend

growthrate, %

Sugar 7.7 Sugarcane: land cultivated. 1873 9.4Wine 5.7 Grapes: land cultivated. 1873 7.5Flour products 5.5 Implicit flour consumption: implicit wheat consump-

tion, assuming 600 kg of flour per ton of wheat, mi-nus exports, plus imports.

1877 7.4

Slaughterhouse 5.4 Exports, total (at 1914 prices): 1875 2.2Hides and skins. 1875 0.9Meat. 1875 4.5Other byproducts. 1875 4.8

plus annual domestic meat consumption of 90 kg perperson, at 80% 1914 export price per kg, based on the assumption that domestic consumption was of lower quality.

1875 2.6

Metallurgy 5.2 Imports of iron and steel in bars and sheets. 1875 9.3Tobaccoproducts

5.2 Tobacco processed: tobacco production, estimated as land cultivated, assuming a yield of 600kg per ha, plus tobacco imports, minus exports.

1875 3.3

Clothing 4.7 Common sewing thread, reels imported. 1883 2.9Beer 3.6 Hops imported. 1876 7.1Flour mills 5.5 Implicit wheat consumption: wheat production, based

on cultivated land, minus exports, plus imports.1877 7.9

Dairy products 3.0 Butter, casein, and cheese exports, plus 1.6 kg of cheese and 1 kg of butter per person per year, minusimports, all valued at 1914 export prices.

1875 5.3

* Value added was calculated from the industrial census by subtracting the cost of rawmaterials from the gross value of output.

Sources:

Census value: CNC, Tercer censo nacional, VII, Censo de las industrias, Buenos Aires, 1917,pp. 27-34.

Cultivated land: DGEE, Estadística Agrícola: 1913-14, p. 18; and CNG, Anuario geográficoargentino, Buenos Aires, 1941, pp. 204, 207, 227, 229, 235, 245.

Exports and imports: F. Latzina, Estadística retrospectiva del comercio exterior argentino1875-1904, Buenos Aires, 1905; and DGEN, Anuario, various years.

Per capita consumption levels: Estimated from Tornquist, Economic Development, pp.272-73; CNG, Anuario geográfico, p. 275.

Population: Recchini de Lattes and Lattes, eds., Población de Argentina, p. 199, Tabla 1.

estimates can be considered reliable, therefore, far more details of his methodology

must be given.

Attempts to extend the official series and their extensions even further back,

meanwhile, are even more problematic. Three are shown in Figure A1.2. Their prob-

- 52 -

lems are as follows:

1) John Coatsworth’s series is based on (partly misreported) estimates of wages

in Buenos Aires,145 which are then projected onto the whole of the country,

even though the high costs of internal transportation make it unlikely that

wage levels in the Littoral were representative of wages in the interior.

2) The new Maddison Project estimate extends the ECLA-della Paolera series

using the nominal value of pastoral output in the Pampean zone, combined

with the assumption that the zone’s non-pastoral sector grew at the same rate,

and that per capita output remained constant in the rest of the country.146 As-

ide from these questionable assumptions, the use of the nominal (silver) value

of pastoral output is dubious because it ignores the sharp fall in (silver) prices

during this period, which means that the nominal value will understate

volume growth.147

3) Victor Bulmer-Thomas’ estimate takes Cortés Conde’s series for 1875-1913,

multiplies it by export and import price indices calculated using prices from

Europe to convert it to nominal values, then extends it back with exports and

tax revenues from Buenos Aires, thereby ignoring the rest of Argentina.148

145. Coatsworth states that ‘Lyman Johnson's Buenos Aires study cites an average monthly wage of17 pesos or 204 pesos per year for urban unskilled construction laborers in the first decade of thenineteenth century’. J.H. Coatsworth, ‘Economic and Institutional Trajectories in Nineteenth-Century Latin America’, in idem and A.M. Taylor, eds., Latin America and the World Economysince 1800, Cambridge, MA, 1998, p. 45. Similarly, he has elsewhere claimed that ‘Johnson citeswages in Buenos Aires ranging from 17 pesos per month (204 pesos per year) for unskilledlabour’. Idem, ‘Economic History and the History of Prices in Colonial Latin America’, in L.L.Johnson and E. Tandeter, eds., Essays on the Price History of Latin America, Albuquerque, 1990,pp. 28-29. Yet nowhere in the referenced study does Johnson give such a figure. See L.L. John-son, ‘The Price History of Buenos Aires During the Viceregal Period’, in Johnson and Tandeter,eds., Essays on the Price History. Moreover, elsewhere Johnson has provided an estimate ofannual wages for urban unskilled construction labourers as from 90 to 105 pesos, dependingupon the assumptions made about the number of days worked. Either way, they are around halfthe level claimed by Coatsworth. L.L. Johnson, ‘Salarios, precios y costo de vida en el BuenosAires colonial tardio’, Boletín del Instituto de Historía Argentina y Americana ‘Dr. E. Ravign-ani’, 2:7, 1990, pp. 139, 145, Cuadros 1 and 2.

146. Bolt and Luiten van Zanden, ‘First Update’, p. 20. Their source for the Littoral’s pastoral outputduring 1825-65 is C. Newland and B. Poulson, ‘Purely Animal: Pastoral Production and EarlyArgentine Economic Growth 1825-1865’, Explorations in Economic History, 35:3, 1998, p. 328,Table 1.

147. On the falling pastoral prices, see J.C. Garavaglia, ‘La economía rural de la campaña de BuenosAires vista a través de sus precios: 1756-1852’, in R. Fradkin and J.C. Garavaglia, eds., En buscade un tiempo perdido: La economía de Buenos Aires en el país de la abundancia, 1750-1865,Buenos Aires, 2004, pp. 119-29. As will be seen in Chapter 4, the prices of imports fell evenfaster, so the terms of trade improved.

- 53 -

Figure A1.2Argentina’s Relative GDP Per Capita, 1800-1913

0

20

40

60

80

100

120

140

1780 1800 1820 1840 1860 1880 1900 1920

Coatsworth (1998)*

Maddison Project (2013)**

Bulmer-Thomas (2012)***

USA = 100

* Maddison’s original estimates for 1870 and 1900, extended back to 1800 using wage data asa proxy for national income.

** Maddison’s original estimates for 1900-13, extended back to 1870 and 1875-1899 usingGerardo della Paolera’s volume indexes of GDP, then back to 1800, 1820, 1850, and 1860,using Carlos Newland and associates’ estimates of pastoral output in the Pampean zone.

*** Current GDP per capita for 1900-13, estimated by multiplying a volume index of GDPwith consumer and wholesale price indices, then extending it back to 1875-1899 using avolume index of GDP multiplied using Argentine and British export prices, then back to1820-1874 using export values and tax revenues as proxies.

Sources: Coatsworth, ‘Economic and Institutional Trajectories’, p. 26, Table 1.1; V. Bulmer-Thomas, ‘The Development Gap Between Latin America and the US: When and Why Did ItArise?’, paper presented at the conference Understanding the Institutional Trajectory of LatinAmerican Development, London School of Economics, 27 September 2012, pp. 41-43, TableA.3.5; also forthcoming as idem, The Economic History of Latin America SinceIndependence, 3rd ed., Cambridge, 2014, Appendices 3 and 4; and Bolt and Luiten vanZanden, ‘First Update’.

These methodologies, as seen in Figure A1.2, produce wildly divergent results, with

Coatsworth suggesting that Argentina’s GDP per capita fell behind that of the United

States, Bulmer-Thomas indicating that it started to catch up, and the Maddison

Project showing that it stayed at roughly 60 to 70 percent the US level. This illus-

trates the margins of error contained in these estimates, which are due to the frag-

148. Bulmer-Thomas, ‘Development Gap’, pp. 5-6. On the problems with using the core’s export andimport prices as proxies for prices in the periphery, see Chapter 2.

- 54 -

mentary data their authors use, as well as the questionable assumptions they must

make to construct them.

- 55 -

Chapter 2

The Long Boom

But it is chiefly in order to purchase European goods, that the colonies part withtheir own produce. The more, therefore, they pay for the one, the less they really getfor the other, and the dearness of the one is the same thing with the cheapness of theother.

Adam Smith, The Wealth of Nations1

This chapter demonstrates that the periphery’s nineteenth-century terms-of-trade

boom was far longer, greater, and more widespread than has previously been

supposed. By revisiting some of the methodological issues raised in the debates

about the Prebisch-Singer Hypothesis,2 it is found that there is a major downward

bias in the trend of most estimates of peripheral countries’ terms of trade in the nine-

teenth century. The problem is that historians have routinely used prices recorded in

the North Atlantic core as proxies for prices in the peripheral countries themselves. It

was precisely this methodological error that originally made Raúl Prebisch and Hans

Singer believe that there had been a long-term deterioration in the periphery’s terms

of trade, and it has also meant that Jeffrey Williamson, more recently, has under-

estimated the length, magnitude, and extent of the terms-of-trade boom that the peri-

phery experienced in the long nineteenth century.3

This chapter provides a comprehensive examination of how the periphery’s

terms of trade have been (and should be) measured, and how this methodological

issue has affected the existing literature. It begins with a detailed discussion of the

old and new narratives about the terms of trade. Following this, the chapter shows

that there is a downward bias in the trend of most estimates of peripheral countries’

1. A. Smith, An Inquiry into the Nature and Causes of the Wealth of Nations, II, New York, (1776)1904, pp. 77-78.

2. Prebisch, ‘Economic Development’; and Singer, ‘Distribution of Gains’.3. Williamson, ‘Globalization and the Great Divergence’; and idem, Trade and Poverty, esp. ch. 3.

- 56 -

nineteenth-century terms of trade, including those used by Williamson. Various tests

for the existence of that bias are conducted using an unusually rich collection of price

series from Indonesia. Finally, the case of India is used to illustrate how correcting

the downward bias makes the periphery’s long terms-of-trade boom seem even more

significant than Williamson supposes. Chapter 3 will then go beyond Williamson to

provide an alternative account of why this long boom drove global divergence.

Old and New NarrativesThe two narratives about the periphery’s (net barter) terms of trade are quite differ-

ent. Prebisch and Singer argued that they had been deteriorating since at least the

1880s, redistributing income from the periphery towards the core. Williamson, by

contrast, contends that a terms-of-trade boom drove the periphery’s deindustrialisa-

tion, leading to the ‘great divergence’. Here each narrative will be discussed in turn.

The Prebisch-Singer HypothesisNeither Prebisch nor Singer was the first to claim that the periphery’s terms of trade

had deteriorated. Since the 1920s the observation had been made by several authors,

with the blame variously placed on the overproduction of primary commodities,

monopolistic practices in industry, and differences in the nature of the demand for

primary commodities and manufactured goods.4 Prebisch and Singer’s contribution

to this debate was twofold. First, based on Singer’s empirical work, they argued that

the interwar deterioration was part of a longer-term process that had been ongoing

since at least the 1880s. Second, from prominent positions in international bureaucra-

cies, they polemicised aggressively that the correct response to the deterioration was

government-sponsored industrialisation, arguing against the liberal belief that peri-

pheral countries should specialise in the production of primary commodities for

export.5

4. For example, G.M. Cassel, Monopolistic Tendencies in Industry and Trade: Being an Analysis ofthe Nature and Causes of the Poverty of Nations, Geneva, 1927; V.P. Timoshenko, ‘World Agri-culture and the Depression’, Michigan Business Studies, 5:5, 1933; G.C. Means, Industrial Pricesand Their Relative Inflexibility, Washington, DC, 1935; and C.P. Kindleberger, ‘InternationalMonetary Stabilization’, in S.E. Harris, ed., Postwar Economic Problems, New York andLondon, 1943. For discussion, see Love, Crafting the Third World, ch. 7; and Toye and Toye,‘Origins and Interpretation’, p. 440.

5. Singer was an Anglo-German economist who held prominent positions in various United Nationsbodies in the 1950s and ‘60s, while Prebisch, an Argentine economist and public official, was

- 57 -

Much of the subsequent debate has revolved around the empirical basis of the

Prebisch-Singer Hypothesis. Singer’s initial contribution was to use British price

series to calculate the terms of trade between manufactured goods and primary

commodities.6 His results indicated that ‘from the latter part of the nineteenth century

to the eve of the Second World War, a period of well over half a century, there was a

secular downward trend in the prices of primary goods relative to the prices of

manufactured goods’.7 Since then, the debate has focused on whether such a deterior-

ation actually took place.8 So far, it has been suggested that there was a deterioration

in the terms of trade for primary-commodity producers during the twentieth century,

although the exact form that it took is unclear. Enzo Grilli and Maw Cheng Yang

made the most important contribution when they appeared to confirm that a deterior-

ation had occurred. By compiling price series for 24 primary commodities from 1900

to the mid-1980s, then deflating them with a price index of the core countries’

manufactured exports,9 they found that ‘the relative prices of all primary commodit-

ies fell on trend by 0.5 percent a year and those of nonfuel primary commodities by

0.6 percent a year’.10 Thereafter, the statistical debate has reflected developments in

econometrics, with particular attention given to the nature of the deterioration. The

principal question has become whether it was due to a statistically significant trend

or one or more ‘structural breaks’.11 The evidence probably favours the latter inter-

prominent in ECLA, then in the United Nations Conference on Trade and Development(UNCTAD). On the origins of the Prebisch-Singer hypothesis and the controversy surrounding it,see Love, ‘Raúl Prebisch’; idem., Crafting the Third World, ch. 8; Shaw, Sir Hans Singer, pp.49-58; Toye and Toye, ‘Origins and Interpretation’; and Dosman, Life and Times, chs. 5-11.

6. Singer’s findings were published in United Nations, Relative Prices, esp. pp. 21-28. Singer drewon the British export and import price series calculated by W. Schlote, British Overseas Trade:From 1700 to the 1930s, Oxford, 1952. Singer also presented a second series that he claimed tobe ‘based on the trade statistics of the major trading countries and a number of others’ (UnitedNations, Relative Prices, p. 21), taken from the League of Nations, Industrialization and ForeignTrade, Geneva, 1945, p. 157, Tables 7 and 8. The methodology of the League of Nations studynevertheless reveals that its principal source was Schlote. Ibid., pp. 154-55. Unsurprisingly,Singer’s two series reinforced each other!

7. United Nations, Relative Prices, p. 7.8. For a recent overview, see Ocampo and Parra, ‘Continuing Relevance’; also see Spraos, Inequal-

ising Trade?, ch. 3; and Diakosavvas and Scandizzo, ‘Trends in the Terms of Trade’.9. E.R. Grilli and M.C. Yang, ‘Primary Commodity Prices, Manufactured Goods Prices, and the

Terms of Trade of Developing Countries: What the Long Run Shows’, World Bank EconomicReview, 2:1, 1988; subsequently updated in S. Pfaffenzeller, P. Newbold and A. Rayner, ‘A ShortNote on Updating the Grilli and Yang Commodity Price Index’, World Bank Economic Review,21:1, 2007.

10. Grilli and Yang, ‘Primary Commodity Prices’, p. 1.11. For example, D. Sapsford, P. Sarkar, and H.W. Singer, ‘The Prebisch-Singer Terms of Trade

Controversy Revisited’, Journal of International Development, 4:3, 1992; M. Bleaney and D.

- 58 -

pretation, although it remains somewhat inconclusive because much depends upon

how the econometric models are calibrated. Unfortunately, the highly technical

nature of the debate has often obscured the basic finding that a deterioration in the

terms of trade most likely did occur in the twentieth century.

Of more relevance here, however, are the critiques of Singer’s claim that the

periphery’s terms of trade had been deteriorating since at least the 1880s. This claim

was soon questioned by P.T. Ellsworth, who pointed out that the price series used by

Singer had been mainly recorded in Britain. This was a problem, Ellsworth observed,

because falling transportation costs during the nineteenth century meant that British

prices did not necessarily reflect the prices paid and received in the peripheral coun-

tries, as the primary-commodity prices included ‘cost, insurance, and freight’ (CIF),

while the prices of manufactured exports were valued ‘free on board’ (FOB).12 Fall-

ing transportation costs meant that the FOB price of a good in the exporting country

and its CIF price in the importing country converged, so it was possible that the CIF

prices of Britain’s imported primary commodities were falling even as the FOB

prices of those goods were increasing in the periphery. Ellsworth concluded that ‘the

apparent relative decline in the prices of primary exports is therefore heavily

weighted by the significant reduction in freight rates. It appears certain that a large

part of the fall in primary product prices in European markets must be attributed to

this cause’.13

Paul Bairoch took Ellsworth’s critique even further. He contended that the

periphery’s terms of trade had in fact improved from the 1870s up to the end of the

1920s.14 To illustrate this, he drew on a range of fragmentary data, including compar-

isons between League of Nations estimates of the FOB and CIF value of world trade;

domestic wholesale prices of primary commodities and manufactured goods; and the

Greenaway, ‘Long-Run Trends in the Relative Price of Primary Commodities and in the Terms ofTrade of Developing Countries’, Oxford Economic Papers, 45:3, 1993; J.T. Cuddington, R.Ludema, and S.A. Jayasuriya, ‘Prebisch-Singer Redux’, Central Bank of Chile Working Paper140, 2002; J.A. Ocampo and M.A. Parra-Lancourt, ‘The Terms of Trade for Commodities in theTwentieth Century’, CEPAL Review, 79, 2003; and idem, ‘The Terms of Trade for Commoditiessince the Mid-19th Century’, Journal of Iberian and Latin American Economic History, 28:1,2010.

12. P.T. Ellsworth, ‘The Terms of Trade between Primary Producing and Industrial Countries’, Inter-American Economic Affairs, 10:1, 1956.

13. Ibid., p. 54.14. P. Bairoch, The Economic Development of the Third World since 1900, London, (1977) 2006, pp.

111-26; also idem., Economics & World History: Myths and Paradoxes, Chicago, 1993, ch. 10.

- 59 -

terms of trade of various primary commodity-exporting countries. His conclusion

was that there had been ‘a probable improvement between the years 1870 and

1926/29 of 20 to 40 per cent in the export prices of primary products relative to

export prices of manufactures’,15 thus refuting the Prebisch-Singer Hypothesis. Bair-

och did not, nevertheless, elaborate on the broader implications of his own findings.

That task would only be taken up later.

Williamson’s NarrativeWilliamson has gone even further than Bairoch, arguing that the periphery’s terms-

of-trade boom had begun early in the nineteenth century.16 This observation is based

on estimates of the terms of trade of 21 peripheral countries from Eastern and South-

ern Europe, the Middle East, Asia, and Latin America. From this database, William-

son constructed an index of the terms of trade of 19 countries, weighting them

according to their populations in 1870.17 China and Japan were the two excluded

because Williamson found that the price of opium rose dramatically, causing a deteri-

oration in China’s terms of trade that, due to the country’s large population, would

have distorted the overall picture if it had been included. For this reason, both China

and Japan (together making up East Asia) where left out of the index, leading to the

series shown in Figure 2.1, where, following Williamson, it is contrasted with

Britain’s terms of trade. The poor periphery’s terms of trade show an increase of 75

percent from the 1800s to the 1860s, which substantially mirrors the deterioration in

Britain’s terms of trade over the same period.18

The first cause of this boom, according to Williamson, was the falling prices

of manufactured goods in the core.19 During Britain’s industrial revolution,

productivity growth pulled down prices because manufacturing was highly competit-

ive, so firms were largely unable to collude or administer their own prices. Even

when patented innovations briefly allowed monopoly profits, rival firms rapidly

15. Bairoch, Economic Development, p. 123.16. Williamson, ‘Globalization and the Great Divergence’; and idem, Trade and Poverty, esp. ch 3.17. Williamson, ‘Globalization and the Great Divergence’, pp. 359-61, 386-91.18. Figure 2.1 is different from the equivalent figures in Williamson’s published works because it

was found in his underlying worksheets that he had accidentally used a series for Latin America,rather than the series for the poor periphery excluding East Asia. This was confirmed byProfessor Williamson in private correspondence with the author on 25 May 2012.

19. Williamson, Trade and Poverty, pp. 25-27, 31-32.

- 60 -

Figure 2.1Williamson’s Terms-of-Trade Boom, 1800-1913

0

20

40

60

80

100

120

140

160

180

200

1800 1820 1840 1860 1880 1900 1920

1900 = 100

Poor periphery, excl. East Asia*

UK

* Average net barter terms of trade of 19 peripheral countries, weighted by their populationsin 1870. The countries are Argentina, Brazil, Ceylon, Chile, Cuba, Egypt, India, Indonesia,Italy, Levant, Malaya, Mexico, Ottoman Turkey, the Philippines, Portugal, Russia, Siam,Spain, and Venezuela.

Source: Data underlying Williamson, ‘Globalization and the Great Divergence’, p. 362,Figure 2; also idem, Trade and Poverty, p. 32, Figure 3.2; kindly provided by ProfessorWilliamson. For the series, see Table DA.2 in the Data Appendix.

began to use the same techniques and technologies, driving down prices due to a

greater supply of the good.20 Given such competition, manufacturers increasingly

looked toward exports as a means of avoiding glut on the domestic market. Hence,

from perhaps a quarter of industrial output in the 1770s, exports rose to about two

thirds by the mid-nineteenth century.21 British industry could conquer foreign

markets by supplying them at dramatically lower prices – the export price of British

cotton piece goods fell by roughly 90 percent from the 1770s to the 1850s,22 driving

20. This was more or less the neo-classical world of ‘perfect competition’. See C.K. Harley, ‘Pricesand Profits in Cotton Textiles During the Industrial Revolution’, Discussion Paper in Economicand Social History 81, Oxford University, 2010.

21. J. Cuenca Esteban, ‘The Rising Share of British Industrial Exports in Industrial Output, 1700-1851’, Journal of Economic History, 57:4, 1997, p. 885, Figure 1.

22. Based on export price data in A.H. Imlah, Economic Elements in the Pax Britannica: Studies inBritish Foreign Trade in the Nineteenth Century, Cambridge, MA, 1958, pp. 208-10, Table 2;B.R. Mitchell, British Historical Statistics, Cambridge, 1988, p. 761; and J. Cuenca Esteban,‘British Textile Prices, 1770-1831: Are British Growth Rates Worth Revising Once Again?’,

- 61 -

the deterioration in Britain’s terms of trade shown in Figure 2.1. Nonetheless, prices

would probably have fallen even further without exports as a result of the glut that

would have formed on the domestic market. For the periphery, the consequence was

lower prices of imported textiles and other manufactured goods, bringing improved

terms of trade.

Price convergence is identified by Williamson as the second cause of the long

boom.23 Before the nineteenth century, goods from the periphery had sold in the core

for far more than in the countries where they were produced.24 Those margins shrank,

however, thanks to the combination of cheaper transportation and trade liberalisation.

Egyptian cotton, for example, sold for around 50 percent more in Liverpool than in

Alexandria during the 1820s and ‘30s, but the margin fell to just five percent by the

1890s.25 Similarly, Indonesian sugar sold for over 100 percent more in London than

in Java in the 1840s, but the margin fell to 23 percent during the decade prior to the

First World War.26 What fragmentary data there are suggest that these trends were

representative of the periphery’s exports in general due to widespread price conver-

gence during the long nineteenth century.27 This contributed to the long boom, Willi-

amson argues, by raising the periphery’s export prices, as they converged upward

with prices in the core.

The result of the boom, for Williamson, was the periphery’s deindustrialisa-

tion.28 In response to the changed price incentives, labour and capital in the periphery

increasingly focused on the export of primary commodities, while the cottage indus-

Economic History Review, 47:1, 1994, pp. 101-02, Table A3.23. J.G. Williamson, ‘Land, Labor, and Globalization in the Third World, 1870-1940’, Journal of

Economic History, 62:1, 2002, pp. 59-62; idem, Globalization and the Poor Periphery, ch. 3; andidem, Trade and Poverty, p. 25. On commodity-price convergence, see K.H. O'Rourke and J.G.Williamson, ‘When Did Globalisation Begin?’, European Review of Economic History, 6:1,2002, pp. 32-39; D. Jacks, ‘Intra- and International Commodity Market Integration in the AtlanticEconomy, 1800-1913’, Explorations in Economic History, 42:3, 2005; idem, ‘What Drove 19thCentury Commodity Market Integration?’, Explorations in Economic History, 43:3, 2006; and D.Jacks, C.M. Meissner, and D. Novyd, ‘Trade Costs in the First Wave of Globalization’, Explora-tions in Economic History, 47:2, 2010.

24. O'Rourke and Williamson, ‘When Did Globalisation Begin?’, pp. 32-35.25. Calculated from C. Issawi, ed., The Economic History of the Middle East 1800-1914: A Book of

Readings, Chicago, 1966, pp. 447-48. For the series, see Table DA.7 in the Data Appendix.26. Calculated from W.L. Korthals Altes, Changing Economy in Indonesia: A Selection of Statistical

Source Material from the Early 19th Century up to 1940, XV, Prices (Non-Rice) 1814–1940,Amsterdam, 1994, pp. 87-96, Table 2A, Series 60, 62, 68 and 69. For the series, see Table DA.7in the Data Appendix.

27. O’Rourke and Williamson, ‘When Did Globalisation Begin?’, pp. 35-39.28. Williamson, Trade and Poverty, ch. 5.

- 62 -

Table 2.1Distribution of World Manufacturing Output, 1750-1913

Britain Rest ofEurope

Europeanoffshoots

Non-European peripheryTotal China India

1750 2 21 0 77 33 251800 4 24 1 71 33 201830 10 25 3 63 30 181860 20 33 8 39 20 91880 23 38 15 23 13 31900 19 44 25 13 6 21913 14 43 33 10 4 1

Note: Totals may not equal 100 due to rounding.

Source: Adapted from Bairoch, ‘International Industrialization Levels’, p. 296, Table 10.

tries that had once supplied the domestic market were destroyed by influxes of

cheaper imports. To demonstrate this process, Williamson presents estimates of how

imports displaced domestic textile production in several countries. In the most

famous case, India was turned from a net exporter of textiles at the beginning of the

nineteenth into a net importer of about 60 percent of its domestic consumption in the

1870s, with other parts of the periphery having similar experiences.29 As a result, the

world’s industrial capacity became concentrated in the North Atlantic core. To illus-

trate this, Williamson presents Bairoch’s widely used estimates of international

industrialisation levels since 1750,30 shown in Table 2.1. They indicate that the non-

European periphery’s share of world manufacturing output fell from perhaps three

quarters during the mid-eighteenth century to a tenth by the First World War. The

periphery’s industrial output per capita actually fell, Bairoch’s estimates suggest, by

around two-thirds over this period.31 Even though these numbers are, Bairoch admits,

partly based on ‘subjective calculations’,32 they can be taken as roughly indicative of

actual trends, as will be seen below for the case of India.33

29. R. Dobado González, A. Gómez Galvarriato, and J.G. Williamson, ‘Mexican Exceptionalism:Globalization and Deindustrialization, 1750-1877’, Journal of Economic History, 68:3, 2008, pp.773-75; and Williamson, Trade and Poverty, pp. 64-65.

30. P. Bairoch, ‘International Industrialization Levels from 1750 to 1980’, Journal of EuropeanEconomic History, 11:1&2, 1982.

31. Ibid., p. 281, Table 4.32. Ibid., p. 317.33. Apart from the case of India, see accounts of the periphery’s deindustrialisation in C. Issawi, An

Economic History of the Middle East and North Africa, London, 1982, pp. 150-54; Ş. Pamuk,The Ottoman Empire and European Capitalism, 1820-1913: Trade, Investment and Production,Cambridge, 1986, ch. 6; R.J. Salvucci, Textiles and Capitalism in Mexico: An Economic History

- 63 -

Williamson’s narrative is, then, that the falling prices of the core’s manufac-

tured goods combined with price convergence to generate a terms-of-trade boom in

the periphery, which led to deindustrialisation. The Prebisch-Singer hypothesis is

thus turned on its head. Whereas their narrative had been concerned with the effect of

the terms of trade on income, Williamson is more concerned with the effect on

incentives. And while Prebisch and Singer claimed that a deterioration in the terms

of trade required industrialisation, Williamson argues that a boom had previously

caused deindustrialisation.

Even though this new narrative is plausible, the evidence that Williamson

presents to support it is not convincing. Most notably, Williamson not only finds that

China’s terms of trade deteriorated, but he also indicates that no boom occurred in

India. Consequently, his narrative does not appear to apply to the main regions

where, according to Bairoch’s numbers, deindustrialisation took place.34 Moreover,

Williamson’s index of the periphery’s terms of trade, shown in Figure 2.1, provokes a

series of unsettling questions: If, as Williamson has contended,35 price convergence

carried on until the end of the century, why did the boom stop around 1860? What

about Bairoch’s claim that the periphery’s terms of trade improved from the 1870s

through to the 1920s? What is more, why do the periphery’s terms of trade look so

suspiciously like Britain’s terms of trade inverted? To address these questions, it is

necessary to look in more detail at some of the methodological issues that have

already been touched upon here.

The Downward BiasTo understand why problems can arise if prices from the core countries are used to

measure peripheral countries’ terms of trade, it is helpful to consider the various

prices paid for an internationally traded good. Assuming that no value is added by

processing, the principal prices are:

of the Obrajes, 1539-1840, Princeton, 1987, ch. 5; A.H. Amsden, The Rise of ‘the Rest’: Chal-lenges to the West from Late-Industrializing Economies, Oxford, 2001, pp. 33-39; and P. van derEng, ‘Why Didn’t Colonial Indonesia Have a Competitive Cotton Textile Industry?’, ModernAsian Studies, 47:3, 2013.

34. Roy, ‘Review of Trade and Poverty’.35. K.H. O'Rourke and J.G. Williamson, Globalization and History: The Evolution of a Nineteenth-

Century Atlantic Economy, Cambridge, MA, 1999, ch. 3; and idem., ‘When Did GlobalisationBegin?’, pp. 37-39.

- 64 -

1) Producer price in the exporting country paid by a merchant to the producer of

the good.

2) Wholesale price in the exporting country charged by the merchant, including

internal transportation costs, wholesaling costs, and a commercial markup.

3) Free on board (FOB) price, with the cost of packaging and delivering of the

good to the ship having been added, including the payment of any export

taxes.

4) Cost, insurance, and freight (CIF) price, including all the trade costs associ-

ated with transporting the good between the two countries, excluding import

tariffs.

5) Wholesale price in the importing country, including the payment of any im-

port taxes, wholesaling costs, and a commercial markup.

6) Retail price in the importing country paid by the consumer, including retail-

ing costs and a further commercial markup.

Which prices are used to calculate a country’s terms of trade depends in part

on what the purpose of the calculation is. The traditional Prebisch-Singer narrative,

especially as formulated by Singer,36 was concerned with the distribution of the gains

from trade, which are arguably best measured using a country’s own prices recorded

when exports leave and when imports arrive at its port.37 Following this logic, a

country’s ‘at-the-port terms of trade’ are calculated as:

NBTTAt the port CIF import price indexFOB export price index

= 2.1

For Williamson’s narrative, by contrast, the terms of trade in a country’s own

domestic prices are more important because he is primarily interested in price incent-

ives within the country, so at the wholesale level the preferred measure would be:

36. Singer, ‘Distribution of Gains’.37. The logic is that these prices are those paid and received in international trade. Whether or not

this is best for testing the Prebisch-Singer hypothesis is questionable because the distribution ofthe gains from trade are often determined by domestic wholesale prices. If, for instance, a coun-try’s trade is monopolised by foreign merchants who use their position to impose high markupson buyers, or if the home government imposes high export or import taxes in order to makepayments to foreign investors, it is less clear that at-the-port prices provide the best measure.

- 65 -

NBTTexport

Wholesale Domestic wholesale import price indexDomestic wholesale price index

= 2.2

The ideal measure of the terms of trade would thus be in a country’s own prices,

whether at the port or within the country.

A country’s own prices are not always available, however, so proxies must be

used. For peripheral countries, in particular, trade statistics are often scarce and of

poor quality, so they cannot be relied upon to provide unit values (that is, the value of

imports or exports divided by their physical quantities) for at-the-port terms of

trade.38 That being so, prices from the core countries have often been used as proxies

for peripheral countries’ own prices – a methodology that Singer himself pioneered

with the use of British trade statistics.39 Subsequent estimates of peripheral countries’

terms of trade have largely followed Singer’s lead,40 producing what can be called

‘proxy terms of trade’, calculated using either unit values or wholesale prices from

the core countries, in this way:

Proxy NBTT ForeignForeign

import price indexexport price index

= 2.3

As Ellsworth realised, proxy terms-of-trade estimates are problematic to the

extent that there are changes in the costs incurred in trading a good. If trade costs

increase over time, they will give an upward bias to the trend of any proxy estimate

because rising trade costs tend to inflate the prices of a country’s exports abroad and

depress them at home, at the same time as they inflate the domestic prices of its

imports and depress them in their country of origin. Falling trade costs will, on the

other hand, give a downward bias to the trend of proxy terms of trade. A notional

illustration of why is seen in Figure 2.2. In this case, trade costs fall for a century, so

the prices of a country’s exports in the importing country fall, even as they go up at

home. At the same time, the prices of its imports go up in the exporting country, even

38. For an exploration of some of the issues, see D.C.M. Platt, ‘Problems in the Interpretation ofForeign Trade Statistics before 1914’, Journal of Latin American Studies, 3:2, 1971.

39. United Nations, Relative Prices, esp. pp. 21-28. Also see page 58, footnote 6.40. The main subsequent reestimation of the periphery’s terms of trade, which substantially replic-

ated Singer’s methodology, was by W.A. Lewis, ‘World Production, Prices and Trade1870-1960’, Manchester School of Economic and Social Studies, 20:2, 1952. For discussion, seeBairoch, Economic Development, pp. 114-15; and Spraos, Inequalising Trade?, ch. 3.

- 66 -

Figure 2.2Prices of an Internationally-Traded Good with Falling Trade Costs

0

20

40

60

80

100

120

Year 1 Year 100

Exp

ortin

g co

untry

Im

porti

ng

coun

try

Note: The figure shows the notional price of an internationally-traded good. It shows howfalling trade costs can mean that the domestic price of a country’s exports can go up, even asthe price of that same good falls in the importing country.

as the prices are falling at home. Hence, any terms of trade calculated using the other

county’s prices will have a downward bias in the trend.

Proxy terms-of-trade estimates are particularly problematic for the nineteenth

century because there was a massive fall in trade costs. Figure 2.3 illustrates the

resulting problem for Egyptian cotton, with the wholesale price in British shillings

per kilo in Alexandria (the thick line) and Liverpool (the thin line) shown for the

periods in which there are data for both cities. The thick line demonstrates that in the

Egyptian port the price was trendless – it fluctuated, in other words, but there was no

general tendency for it to go up or down. But falling trade costs meant that at the

same time the price of Egyptian cotton in Liverpool fell at a trend rate of -0.5 percent

per year, as the prices in the two places converged. Using the Liverpool price as a

proxy for the prices of Egypt’s cotton exports would therefore give a downward bias

in the trend of the country’s terms of trade, leading to an inaccurate representation of

what really occurred.

Evidence of a systematic downward bias in the trend of proxy terms-of-trade

- 67 -

Figure 2.3Price of Egyptian Cotton in Alexandria and Liverpool, 1824-1889

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1820 1830 1840 1850 1860 1870 1880 1890 1900 1910

Liverpool Trend: -0.5% p.a.

Alexandria Trend: 0.0% p.a.

s. per kg

Note: Quantars were converted to kilos at 54.7 kg per quantar during 1824-35, then 44.9 kgper quantar during 1836-99. The exponential trends are indicated by the dashed lines.

Sources:

Prices and conversion factor: Issawi, Economic History: A Book of Readings, pp. 447-48,518.

US$-£ exchange rate: L.H. Officer, ‘Dollar-Sterling Exchange Rates: 1791–1914’, in S.B.Carter et al, eds., Historical Statistics of the United States: Earliest Times to the Present:Millennial Edition, New York, 2006, Series Ee618, available online at http://hsus.cambridge.org/HSUSWeb/HSUSEntryServlet (accessed 20 November 2013).

For the series, see Table DA.7 in the Data Appendix.

estimates comes from comparing them with own-price estimates. Figure 2.4 provides

such evidence for six peripheral countries for which it proved possible to find both

proxy and own-price estimates in the existing literature. At-the-port estimates calcu-

lated using unit values from trade statistics were found for four countries: Canada,41

China,42 Italy,43 and Japan;44 and estimates calculated with wholesale prices were

41. Implicit Paasche indices, from K.W. Taylor and H. Michel, Statistical Contributions to CanadianEconomic History, II, Toronto, 1931, pp. 18-19; also reproduced in F.H. Leacy, Historical Statist-ics of Canada, 2nd ed., Ottawa, 1983, Series G388, online at http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?catno=11-516-XIE&lang=eng (accessed 24 April 2011).

42. Chained Fisher ideal indices, first calculated by F.L. Ho, Index Numbers of the Quantities andPrices of Imports and Exports and of the Barter Terms of Trade in China, 1867-1928, Tientsin,1930; subsequently corrected for or a change in the method of valuing exports and imports in1904 by C. Hou, Foreign Investment and Economic Development in China 1840-1937,

- 68 -

found for another two: India,45 and Indonesia.46 For all six, the proxy estimates were

mainly produced using a mixture of British and US unit values and wholesale

prices.47 The comparison between the own-price and proxy estimates (respectively

the thick and thin lines in Figure 2.4) clearly illustrates the downward bias in the

trend of the latter. In five out of six cases, the bias is sufficient to make it seem like

the terms of trade were deteriorating, even though the own-price series suggest that

they were improving. Table 2.2 confirms this by disaggregating both the proxy and

own-price series into trend and cyclical components, then correlating them for each

country. The result confirms the negative correlation between the trends in the proxy

and own-price estimates for five countries, whereas only two countries have positive

correlation coefficients above 0.50 for the cyclical components. This confirms, then,

that proxy estimates have a downward bias in the trend that is often sufficient to

make it seem like a country’s terms of trade were deteriorating, even though they

were actually improving.

Williamson nevertheless claims to have avoided the downward bias because

Cambridge, MA, 1965, pp. 194-98.43. Fisher ideal indices, from G. Federico and M. Vasta, ‘Was Industrialization an Escape from the

Commodity Lottery? Evidence from Italy, 1861-1940’, Dipartimento di Economia PoliticaQuaderno 573, Università degli Studi di Siena, 2009, pp. 22-23, Table 2; also see G. Federico, S.Natoli, G. Tattara, and M. Vasta, Il commercio estero italiano 1862-1950, Rome, 2011, pp. 74-76,226-32.

44. Chained implicit Paasche indices, from I. Yamazawa and Y. Yamamoto, Estimates of Long-TermEconomic Statistics of Japan since 1868, XIV, Foreign Trade and Balance of Payments, Tokyo,1979, pp. 169-70, 193, 197. These are not strictly own-price measure estimates because importsprior to 1903 were valued FOB and not CIF. Nevertheless, considerable effort was made by theestimate’s authors to convert the FOB figures to CIF using a shipping freight-rate index.

45. Newly estimated chained geometric Laspeyres indices, calculated using prices published by theBritish colonial authorities for 29 exports and 10 imports, with weights taken from trade statist-ics. See Appendix 2.2 for full details.

46. Chained Laspeyres indices, from Korthals Altes, Changing Economy, XV, pp. 158-60.47. Five of the proxy estimates were calculated as chained Laspeyres indices by Williamson and his

co-authors, largely using British price series for the peripheral countries’ exports, and a mixtureof British export prices and US wholesale prices for their imports. See C. Blattman, J. Hwang,and J.G. Williamson, ‘The Impact of the Terms of Trade on Economic Development in the Peri-phery, 1870-1939: Volatility and Secular Change’, NBER Working Paper 10600, 2004, pp. 30-32;and Williamson, ‘Globalization and the Great Divergence’, p. 386-91. Blattman, Hwang, andWilliamson do not appear to have made adjustments for trade costs, even though they promisedthat ‘[i]n a moment we will discuss the adjustments made to our terms of trade figures to accountfor transport cost changes’ (‘Impact of the Terms’, p. 32). Judging from the underlying work-sheets, it would appear that the adjustments were never made. They are available online at http://chrisblattman.com/documents/data/commod/Commoity%20price%20indices%201865-1950.zip(accessed 4 July 2012). The only proxy series not to come from Williamson and his associates isfor Italy, which was calculated using British trade statistics by I.A. Glazier, V.N. Bandera, andR.B. Berner, ‘Terms of Trade between Italy and the United Kingdom 1815–1913’, Journal ofEuropean Economic History, 4:1, 1975, pp. 30-33, Table 5.

- 69 -

Figure 2.4Own-Price and Proxy Terms of Trade, 1860s-1913

20

40

60

80

100

120

140

160

180

1860 1880 1900 1920

Canada

Blattman et al 0.0% p.a.

Taylor & Michell +1.0% p.a.

1913 = 100

20

40

60

80

100

120

140

160

180

1860 1880 1900 1920

China

Williamson +0.2% p.a.

Ho/Hou +0.9% p.a.

20

40

60

80

100

120

140

160

180

1860 1880 1900 1920

India

Williamson -0.4% p.a.

New +0.8% p.a.

20

40

60

80

100

120

140

160

180

1860 1880 1900 1920

Indonesia

Blattman et al -0.4% p.a.

Korthals Altes +2.2% p.a.

20

40

60

80

100

120

140

160

180

1860 1880 1900 1920

Italy

Glazier et al -0.6% p.a.

Federico & Vasta +0.1% p.a.

20

40

60

80

100

120

140

160

180

1860 1880 1900 1920

Japan

Blattman et al -0.4% p.a.

Yamazawa & Yamamoto +1.1% p.a.

Note: The thick lines are own-price terms of trade, the thin lines are proxy terms of trade. Theannual trends are calculated as the rate of change of the exponential trend line.

Sources: See the text. For the series, see Table DA.3 in the Data Appendix.

only six of the 21 series he gathered were proxy estimates, with the other ‘15 taken

from country-specific sources, which do an excellent job in constructing estimates

which come close to the ideal measure’,48 that is, to using the periphery’s own prices.

48. Williamson, ‘Globalization and the Great Divergence’, p. 360; also see idem, Trade and Poverty,

- 70 -

Table 2.2Own-Price and Proxy Terms of Trade, 1860s-1913

Period

Pearson correlation coefficients

WholeComponents*

Trend CyclesCanada 1869-1913 -0.09 -0.22 -0.03China 1867-1913 0.33 0.70 -0.35India 1861-1913 -0.26 -0.84 0.53Indonesia 1865-1913 0.14 -0.17 0.67Italy 1862-1913 -0.25 -0.15 0.27Japan 1875-1913 -0.32 -0.83 0.22

* The trend and cyclical components were separated using a Hodrick-Prescott Filter, with thesmoothing parameter set at 300.

Note: 1.00 equals perfect positive correlation, -1.00 perfect negative correlation.

Source: As in Figure 2.4.

Yet an extensive review of the methodology and sources underlying each of his 21

series, which will be detailed at length in Appendix 2.1, indicates that he is mistaken.

Summarised in Table 2.3, the review finds that only two of Williamson’s 21 series

are own-price estimates, while fully 12 were mainly estimated using proxy prices.

Three more were calculated as ‘part-proxy terms of trade’, using own prices for

exports but foreign prices for imports,49 as follows:

Part proxy NBTT ForeignDomestic

import price indexexport price index

= 2.4

Another two were calculated using the core’s prices as proxies, as in Equation 2.3,

but adjusting them for changes in trade costs, which produces ‘adjusted proxy terms

of trade’, calculated in this way:

Adjusted proxy NBTT ForeignForeign

import price index trade costsexport price index – trade costs

= + 2.5

p. 29. The 21 series include China and Japan, which were excluded from the series for the poorperiphery reproduced in Figure 2.1.

49. Own-price series for the periphery’s exports tend to be far more abundant than those for itsimports; hence, the part-proxy estimates have always used the own-prices for exports and foreignprices for imports. They should have considerably less downward bias because price convergencewould only affect the foreign import price index.

- 71 -

Table 2.3Williamson’s 21 Terms-of-Trade Series

Type of estimate Countries (number)Mean trendgrowth rate,1870-1913

Own-price Indonesia, and Japan (2). 1.39Proxy Argentina, Ceylon, China, Cuba, India, Italy, Malaya, Mexico, the

Philippines, Russia, Siam, and Venezuela (12).-0.47*

Part-proxy Brazil, Egypt, and the Levant (3). 0.13Adjusted proxy Ottoman Turkey, and Spain (2). -0.27Other Chile, and Portugal (2). 0.40

* Excludes Cuba and Malaya due to insufficient data.

Sources: See Appendix 2.1; the series are in Table DA.2 in the Data Appendix.

Of the two remaining series, one (Portugal) is, by the admission of its own author, of

little analytical value, and the last (Chile) is estimated from a variety of sources,

some of which inspire little confidence.

This dependence on proxy estimates suggests that Williamson must have

greatly understated the periphery’s terms-of-trade boom. Much like Singer before

him, Williamson has used prices from the core, particularly from Britain and the

United States, as proxies for prices in the periphery. This is why the index of the peri-

phery’s terms of trade in Figure 2.1 so closely resembles an inverted version of

Britain’s terms of trade. In effect, Williamson has simply produced a mirror image of

Britain’s terms of trade by substantially relying on British CIF prices for the peri-

phery’s exports and British FOB prices for its imports. The boom he detects, there-

fore, is merely the reflection of the deterioration of Britain’s terms of trade due to the

falling prices of its exports up to 1860. Were the effects of price convergence also

taken into account, the boom would most likely appear considerably longer, greater,

and more widespread than Williamson imagines.

To strengthen this conclusion, tests can be run using data from Indonesia, a

peripheral country with an unusually rich collection of price series. Indeed, no other

peripheral country can rival the database of wholesale prices that Dutch researchers

have compiled for Indonesia, principally by drawing on the East Indies’ commercial

press.50 They have used those prices to calculate export and import price indices for

Indonesia since 1825, which results in by far the longest own-price terms of trade

50. Korthals Altes, Changing Economy, XV.

- 72 -

Figure 2.5Indonesia’s Own-Price Terms of Trade, 1825-1913

0

20

40

60

80

100

120

1820 1840 1860 1880 1900 1920

1913 = 100

Sources: Calculated from the export and import price indices in Korthals Altes, ChangingEconomy, XV, pp. 159-60. For the series, see Table DA.4 in the Data Appendix.

estimate for a peripheral country. Their export price index consists of the wholesale

prices of coffee, copra, rubber, sugar, and tobacco, with weights changed every

decade; their import price index mainly consists of cotton piece goods, but also

copper sheets and iron, with the weights adjusted more sporadically.51 Dividing the

export price index by the import price index gives a terms-of-trade series that, as

seen in Figure 2.5, has a roughly 700 percent improvement from the second half of

the 1820s up to the decade prior to the First World War. This, it must be stressed

again, is the longest own-price estimate of a peripheral country’s terms of trade, so

the magnitude and length of the boom that it shows is especially significant.

The price data underlying the terms-of-trade series in Figure 2.5 can be used

to test for the downward bias in proxy estimates. A simple two-good test has the

advantage of bypassing questions relating to the type of price index used and the

composition of the indices.52 These questions are irrelevant in a two-good test

51. Ibid., pp. 161-64.52. These questions have been given much attention in the existing literature on the periphery’s terms

of trade, generally to the detriment of the far more important issue of where the prices were takenfrom. For example, Ş. Pamuk, ‘Foreign Trade, Foreign Capital and the Peripheralization of the

- 73 -

because no indexing takes place. Instead, the relative prices of just two goods in

Indonesia can be compared with the relative prices of the same goods in a core coun-

try. In this way, a two-good test isolates the issue of whether or not the prices from

the core country can be used as proxies for prices in the peripheral country.

Figure 2.6 presents the basic data to be used in the test. It compares the prices

of cotton shirtings in Britain and Indonesia in Panel (a), and the prices of raw sugar

in Britain and Indonesia in Panel (b), with all converted to British currency and

metric units.53 The result illustrates how the prices of cotton piece goods fell much

more dramatically in Indonesia than in Britain, while the opposite was the case for

the price of sugar, which fell more in Britain. The gap between the two series thus

narrowed, indicating substantial price convergence.

These four series can be used to calculate own-price and proxy estimates of

the terms of trade for the two goods, shown respectively as Panels (a) and (b) in

Figure 2.7, with the downward bias in the proxy estimate clearly evident. In Panel (a)

the terms of trade show that, measured in wholesale prices in Java, the purchasing

power of a kilo of sugar increased from around 0.7 m2 of cotton shirtings in the

1840s to 1.2 m2 in the 1890s, then fell back to 0.7 m2 in the 1900s. By contrast, Panel

(b) shows the purchasing power of a kilo of sugar, measured using prices in Britain,

persistently falling from 2.8 m2 to 1.2 m2 in 1900s. Hence, even though the own-price

estimate has the terms of trade improving for much of the nineteenth century, the

proxy estimate indicates a secular deterioration – clear evidence of a major down-

ward bias in the trend.

This two-good test can also be used to evaluate the other methods that have

been used to estimate the terms of trade in the existing literature. In Panel (a) of

Figure 2.8 the thick line is what was described above as a ‘part-proxy’ estimate,

calculated using prices for sugar in Java and cotton shirtings in Manchester. The

Ottoman Empire’, PhD diss., University of California, 1978, pp. 259-73; and L. Prados de laEscosura, ‘Las relaciones reales de intercambio entre España y Gran Bretaña durante los siglosXVIII y XIX’, in P.M. Aceña and L. Prados de la Escosura, eds., La nueva historia económica enEspaña, Madrid, 1985, pp. 129-31.

53. These prices should be treated as close approximations because measuring prices across time iscomplicated by changes in the quality of goods, especially in the case of cotton shirtings. InPanel (a) of Figure 2.6 the actual prices of cotton shirtings has been used for both places during1908-13, then extrapolated backward using the prices of other types of cotton shirtings or cloths.Consequently, the prices prior to 1908 are estimates with some margin of error that are probablyinsufficient to affect the results of the test.

- 74 -

Figure 2.6Prices in Britain and Indonesia, 1836-1913

0

2

4

6

8

10

12

14

1820 1840 1860 1880 1900 1920

d per m2

(a) Cotton shirtings

Java

UK

0

2

4

6

8

10

12

14

1820 1840 1860 1880 1900 1920

d per kg

(b) Raw sugar

Java

UK

Note: The series are in British sterling. There were 20 shillings (s) per pound (£), and 12pennies (d) per shilling. The series were constructed as follows:

Cotton shirtings in Java: Longfold, white English shirtings for 1908-13, extrapolated backthrough ratio splicing with another series for white English shirting during 1861-1908, and aseries for bleached Dutch calicoes (madapollams) during 1836-61. All series are wholesaleprices in Batavia.

Cotton shirtings in Britain: 16 by 15 thread shirtings for 1908-13, extrapolated back throughratio splicing with Lars Sandberg’s grey cloth price index for 1836-1908. Both series arewholesale prices in Manchester.

Raw sugar in Java: Sugar in Batavia for 1848-1913, extrapolated back through ratio splicingwith another series for sugar in Java for 1836-48. Both series are wholesale prices.

Raw sugar in London: Sugar in London throughout. The series is the ‘in bond’ (that is, CIF)price.

Sources:

Cotton shirtings in Java: Korthals Altes, Changing Economy, XV, pp. 27-31, Table 1A, Series27.

Cotton shirtings in Manchester: Economist, ‘Commercial History’, supplement, various years;L.G. Sandberg, ‘Movements in the Quality of British Cotton Textile Exports, 1815-1913’,Journal of Economic History, 28:1, 1968, pp. 8, 10-11, Tables 1, 2, and 4; and Korthals Altes,Changing Economy, XV, p. 31, Table 1A, Series 60.

Raw sugar in Java: Korthals Altes, Changing Economy, XV, pp. 87-96, Table 2A, Series 27,60, 62.

Raw sugar in London: Economist, ‘Commercial History’, supplement, various years; andKorthals Altes, Changing Economy in Indonesia, XV, pp. 27-31, 87-96, Table 2A, Series 68and 69.

Exchange rate: J.T.M. van Laanen, Changing Economy in Indonesia, VI, Money and Banking1816-1940, The Hague, 1980, pp. 123-26, Table 8, Lines 4 and 16.


resulting terms of trade are still some distance from the wholesale estimate, which is

shown by the thin line. Considerably closer is the thick line in Panel (b), in which the

- 75 -

Figure 2.7Two-Good Terms of Trade for Indonesia, 1836-1913

0.0

0.5

1.0

1.5

2.0

1820 1840 1860 1880 1900 1920

m2!

(a) Wholesale 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

1820 1840 1860 1880 1900 1920

(b) Proxy

Note: The series show the purchasing power of a kilo of raw sugar in terms of square metresof cotton shirtings. They are calculated using the following series from Figure 2.6:

(a) Wholesale prices of raw sugar in Java divided by wholesale price of cotton shirtings inJava.

(b) ‘In bond’ price of raw sugar in London divided by wholesale price of cotton shirtings inManchester.

Sources: As in Figure 2.6.

proxy estimate has been adjusted by using an Indonesia-to-Europe freight-rate index

to deduct trade costs from the British price of sugar and add them to the British price

of cotton shirtings, following Equation 2.5. The adjusted proxy estimate that results

suggests that, when own-price estimates are impossible, making such adjustments is

highly desirable, since it leads to terms of trade that are much closer to the wholesale

estimate, again shown by the thin line. More desirable still, however, is what can be

called the ‘adjusted part-proxy terms of trade’ shown in Panel (c). It was calculated

using Indonesia’s own prices for sugar and adjusted British cotton shirtings prices, as

follows:

Adjusted part proxy NBTT ForeignDomesticimport price index trade costs

export price index= + 2.6

Panel (c) indicates that such an estimate should result in a series that is very close to

the wholesale estimate.

The two-good test suggests, then, that proxy estimates are misleading and that

adjusted estimates are preferable. This is confirmed by the simple statistical analysis

- 76 -

Figu

re 2

.8O

ther

Tw

o-G

ood

Term

s of T

rade

for I

ndon

esia

, 183

6-19

13

0.0

0.5

1.0

1.5

2.0

2.5 18

20

1840

18

60

1880

19

00

1920

m2 ! Who

lesa

le P

roxy

0.0

0.5

1.0

1.5

2.0

2.5 18

20

1840

18

60

1880

19

00

1920

0.

0

0.5

1.0

1.5

2.0

2.5 18

20

1840

18

60

1880

19

00

1920

Not

e:Th

ese

ries

show

the

purc

hasi

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wer

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ofsq

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met

res

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eth

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ate.

For

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es w

ere

calc

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sing

the

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win

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Fig

ure

2.6:

(a) W

hole

sale

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f raw

suga

r in

Java

div

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by

who

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Man

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(b)‘

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sale

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cotto

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Man

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both

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and

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The

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the

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the

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in M

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(c) W

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re 2

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Frei

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x: K

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59-6

0.

- 77 -

Table 2.4Indonesia’s Two-Good Terms of Trade, 1836-1913

Pearson correlation coefficients

WholeComponents*

Trend CyclesProxy 0.15 -0.19 0.61Part-proxy 0.67 0.49 0.81Adjusted proxy 0.73 0.91 0.48Adjusted part-proxy 0.91 0.96 0.81

* The trend and cyclical components were separated using a Hodrick-Prescott Filter, with thesmoothing parameter set at 300.

Note: In all cases the coefficients are for the correlation between the wholesale estimate andthe estimates from Figures 2.7 and 2.8. 1.00 equals perfect positive correlation, -1.00 perfectnegative correlation.

in Table 2.4, in which all the estimates and their trend and cyclical components are

correlated with the wholesale estimate during 1836-1913. The coefficients confirm

the negative correlation between the trends in the wholesale and proxy estimates,

while the cycles in all the estimates are positively correlated with the cycles in the

wholesale estimate, although the coefficient is notably lower for the adjusted proxy

estimate. The adjusted part-proxy estimate’s superiority is clearly seen in the high

coefficient for the whole series, as well as for both its trend and cyclical components.

Whenever own-price estimates are not available, therefore, proxy or part-proxy

estimates should be adjusted for changes in trade costs.

The problem, unfortunately, is that making such adjustments is not easy.

Traditionally it has been assumed that trade costs were equivalent to just insurance

and freight,54 yet more recent research on nineteenth-century price convergence has

suggested that trade costs should also include not only ‘storage costs, tariffs, taxes,

and spoilage’, but also ‘exchange rate risk, prevailing interest rates, and/or the risk

aversion of agents’,55 as well as, it can be added, the degree of competition among

merchants, which determines the markups on their goods. Furthermore, there is the

added problem of variation in the degree to which trade costs fell for different places.

Figure 2.9 illustrates this by comparing three freight-rate indices. Whereas the

54. For example, Pamuk, ‘Foreign Trade, Foreign Capital’, pp. 187-99; and L. Prados de la Escosura,‘El comercio hispano-británico en los siglos XVIII y XIX: I. Reconstrucción’, Revista deHistoria Económica, 2:2, 1984, pp. 134-37.

55. Jacks, ‘Intra- and International Commodity Market’, p. 384, fn. 1.

- 78 -

Figure 2.9Freight-Rate Indices, 1800-1913

0

200

400

600

800

1000

1200

1400

1800 1820 1840 1860 1880 1900 1920

1913 = 100

USA to Europe*

Indonesia to Europe**

Baltic to UK***

* Freight rates for ashes, bark, cotton, flour, naval stores, rice, timber, tobacco, and wheat.

** Freight rates for sugar and unspecified cargoes.

*** Freights rates for timber and wheat.

Note: All indices represent freight rates in nominal pounds sterling.

Sources:

Baltic: Calculated from C.K. Harley, ‘Ocean Freight Rates and Productivity, 1740-1913: ThePrimacy of Mechanical Invention Reaffirmed’, Journal of Economic History, 48:4, 1988, pp.873-75, Table 9; and Mohammed and Williamson, ‘Freight Rates’, pp. 179-81, Table 1.

Indonesia: Korthals Altes, Changing Economy, XV, pp. 159-60; and van Laanen, ChangingEconomy, VI, pp. 122-26, Table 8.

United States: D.C. North, ‘The Role of Transportation in the Economic Development ofNorth America’, in Colloque International d’Histoire maritime, ed., Les grandes voiesmaritimes dans le monde, XVe-XIXe siècles, Paris, 1965, p. 236, Table 2; and Officer, ‘Dollar-Sterling Exchange Rates’. For the series, see Table DA.8.

Indonesia-to-Europe index fell by 93 percent from the 1840s to the 1900s, the United

States-to-Europe index fell by 77 percent, and the Baltic-to-Britain index by 60

percent. Freight rates thus fell by different degrees for different places,56 and it can be

assumed that other trade costs did too. This implies that the good results for the

adjusted estimates in Figure 2.8 owe much to the existence of a freight-rate index for

56. Also see S.I.S. Mohammed and J.G. Williamson, ‘Freight Rates and Productivity Gains in BritishTramp Shipping 1869-1950’, Explorations in Economic History, 41:2, 2004.

- 79 -

Indonesia, which again reflects the unusually rich data available for this country.

Unfortunately, freight-rate indices going back to the first half of the nineteenth

century are not currently available for other peripheral countries.

What the available evidence indicates, then, is that there must be a major

downward bias in most of the terms-of-trade series used by Williamson. Here this

was seen for six countries in Figure 2.4, where their own-price and proxy estimates

were compared; then a more detailed and long-term analysis was made using the

price data from Indonesia, which are by far the best price data available for any peri-

pheral country. The two-good test calculated with Indonesia’s prices demonstrated

that the downward bias in the trend of proxy estimates must be large for the nine-

teenth century; it is likely to be present in the part-proxy estimates that Williamson

uses; and possibly even his adjusted proxy estimates have not had sufficient adjust-

ments made. Indonesia’s price data in this way suggest that had Williamson’s estim-

ates used prices taken from the peripheral countries themselves (or had they been

correctly adjusted for trade costs), they would have shown a far longer, greater, and

more widespread terms-of-trade boom than he supposes. Many of the details of

Williamson’s narrative must accordingly be treated with considerable scepticism.

Here this will be illustrated using the crucial case of India.

India’s DeindustrialisationIndia has long been thought of as the principal case of the periphery’s nineteenth-

century deindustrialisation. It has inspired much debate among historians.57 At issue

is the extent to which cheap imported textiles undermined India’s cottage industries.

Table 2.5 illustrates this deindustrialisation with the latest estimates of India’s textile

production during the nineteenth century. They suggest that home production fell

from more or less all of domestic consumption in 1795 to just 40 percent by 1900,

while per capita output fell from five square metres in 1795 to three in 1880,

although it then recovered to four by 1900. Constructing such numbers entails

making heroic assumptions about population and consumption levels, yet these

estimates are particularly important because they were produced by a historian who

is sceptical about claims of India’s deindustrialisation.58 For this reason, it is notable--

57. For overviews, see Habib, ‘Studying a Colonial Economy’; Roy, Rethinking Economic Change,ch. 5; and Parthasarathi, ‘Historical Issues’.

- 80 -

Table 2.5Cotton Cloth Production in India, 1795-1900

Production of cotton cloth

% ofconsumption m2 per capita

1795 78-102 5.01820 102 4.81840 86 4.41860 56 4.11880 38 2.91900 40 4.0

Sources: Calculated from T. Roy, ‘Consumption of Cotton Cloth in India, 1795-1940’,Australian Economic History Review, 52:1, 2012, pp. 73-74, Tables 3 and 5.

that they imply a fall in the per capita output of textiles due to greater competition

with imports.

India’s deindustrialisation is a problem for Williamson’s narrative because he

does not find that the subcontinent experienced a terms-of-trade boom; rather, he

found that its terms of trade were trendless during the long nineteenth century. Willi-

amson must accordingly explain why deindustrialisation occurred without improved

terms of trade. He and his co-author, David Clingingsmith, contend that the combina-

tion of war, pestilence, and drought undermined agricultural productivity, which

drove up the intersectoral terms of trade between agriculture and industry, leading to

deindustrialisation.59 What they call the ‘external’ terms of trade did not play a role in

this narrative.60 On this basis, the long boom’s capacity to explain deindustrialisation

in the periphery appears limited, especially since Williamson has also found that

China’s terms of trade actually deteriorated. Given that these two countries made up

the vast bulk of the periphery’s industry prior to the nineteenth century, the relevance

of the long boom to the periphery’s deindustrialisation seems minimal.61

The case of India becomes less problematic, however, once own-price--

58. See Roy, Rethinking Economic Change, ch. 5.59. D. Clingingsmith and J.G. Williamson, ‘Deindustrialization in 18th and 19th Century India:

Mughal Decline, Climate Shocks and British Industrial Ascent’, Explorations in EconomicHistory, 45:3, 2008; also see Williamson, Trade and Poverty, ch. 6.

60. The use of the adjective ‘external’ is problematic because some use it to describe what have herebeen called ‘at the port’ estimates, while others, including Williamson in this case, use it as short-hand for proxy estimates, implicitly justifying them by claiming that they represent ‘external’ or‘world’ prices.

61. Roy, ‘Review of Trade and Poverty’.

- 81 -

Figure 2.10Three Estimates of India’s Terms of Trade

0

20

40

60

80

100

120

140

160

180

200

1800 1820 1840 1860 1880 1900 1920

1913 = 100 Clingingsmith & Williamson

Official

New

Sources: Data underlying Clingingsmith and Williamson, ‘Deindustrialization in 18th and19th Century India’; kindly provided by Professor Williamson; and DCIS, Index Numbers ofIndian Prices 1861-1931, Delhi, 1932, p. c, Summary Table 1; and Appendix 2.2. For theseries, see Table DA.5.

estimates of its terms of trade are considered. Clingingsmith and Williamson depend

on a proxy estimate, mainly calculated from British and US prices,62 that, as seen in

Figure 2.10, is at odds with two own-price estimates for 1861-1913. Both the own-

price estimates are calculated from dozens of wholesale prices recorded by the Brit-

ish authorities in several Indian cities. The first uses crude export and import price

indices that were calculated as unweighted arithmetic means by those authorities; the

second has been newly constructed for this dissertation using the same wholesale

prices but combining them in more sophisticated chained weighted geometric

Laspreyes indices, as will be detailed in Appendix 2.2. Whereas Williamson’s proxy

estimate is trendless, both the own-price estimates have strong upward trends until

the late 1870s, only becoming trendless thereafter. This leaves the impression that

Williamson’s failure to find a terms-of-trade boom for India may have been due to

the downward bias in the trend of his proxy estimates.

62. Clingingsmith and Williamson, ‘Deindustrialization in 18th and 19th Century India’, pp. 231-32.Also see Appendix 2.1, page 88.

- 82 -

Figure 2.11Terms of Trade for Cotton and Cotton Shirtings in India, 1815-1913

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1800 1820 1840 1860 1880 1900 1920

kg

Part proxy**

Wholesale*

* Wholesale price of raw cotton in Bombay divided by the wholesale price of imported greyshirtings in Calcutta.

** Wholesale price of raw cotton in Bombay divided by wholesale price of shirtings inManchester.

Note: The series show the purchasing power of one kilo of raw cotton in terms of kilos ofcotton shirtings.

Sources:

Cotton price in India during 1813-43: Select Committee on the Growth of Cotton in India,‘Report’, in Parliamentary Papers, IX, 511, 1847-48, pp. 375-76.

Cotton and shirtings prices in India during 1861-1913: DCIS, Index Numbers, pp. 7, 9, Table5.

Exchange rates: DCIS, Index Numbers, p. 18, Table 9; and M.A. Denzel, Handbook of WorldExchange Rates, 1590-1914, Farnham, 2010, pp. 53-54, Table 1.3.1.

Shirtings in Manchester: as in Figure 2.6.


What price data that are available for India support the impression that it

experienced a long terms-of-trade boom. Figure 2.11 gives a pertinent example: the

terms of trade of raw cotton and cotton shirtings. The thick line is an own-price

estimate calculated using wholesale prices in India, while the thin line is a part-proxy

estimate calculated from the wholesale price of raw cotton in Bombay and the price

of shirtings in Manchester. The longer, part-proxy estimate suggests that the purchas-

- 83 -

ing power of a kilo of raw cotton in Bombay increased from around 140 grams of

cotton shirtings in the second half of the 1810s to 520 grams in the 1880s – an

improvement in the terms of trade of 271 percent, and even this is likely to be an

underestimate thanks to the downward bias that exists in the trend of part-proxy

estimates for the nineteenth century.63

The case of India therefore illustrates why the methodological issues

discussed in this chapter matter: how the terms of trade are measured can affect the

analysis that is made. In Williamson’s case, a dubious proxy estimate leads him to

undermine his own narrative with an account of how war, pestilence, and drought,

rather than the terms of trade, caused India’s deindustrialisation. Nevertheless, once

the country’s own prices, rather than proxy prices, are examined, it can be seen that

India’s terms of trade probably did improve, so its deindustrialisation can be

explained by the long boom. Williamson’s alternative account then becomes unne-

cessary, and his central narrative of how improved terms of trade caused deindustrial-

isation in the periphery is greatly reinforced.

Whither Ricardo?This chapter has argued that the periphery’s nineteenth-century terms-of-trade boom

has been greatly under-appreciated as a result of a major methodological error in the

existing literature. When measuring the terms of trade in the nineteenth century,

prices from the core countries should not be used as proxies for prices in the peri-

phery, unless adjustments are made for price convergence due to falling trade costs,

as well as the different degrees to which they fell for different places. The implica-

tion is that were more own-price or correctly adjusted proxy estimates available, the

periphery’s nineteenth-century terms-of-trade boom would appear considerably

longer, greater, and more widespread than has previously been supposed.

In making this argument, the chapter has strengthened Williamson’s new

narrative about the terms of trade, but only by criticising the empirical evidence that

63. Other data on cotton cloth and raw cotton prices that support this conclusion are presented inAllen, Global Economic History, pp. 59-60, Figures 12 and 13. The sources of Allen’s data arenot given, however, so they should be treated with caution. Unfortunately, most recent researchon the price history of India has focused on living standards rather than the terms of trade. See,most notably, idem, ‘India in the Great Divergence’, in T.J. Hatton, K.H. O’Rourke, and A.M.Taylor, eds., The New Comparative Economic History: Essays in Honor of Jeffrey G. Williamson,London, 2007.

- 84 -

he has presented to support it. Proxy estimates, to reiterate, cannot be used to meas-

ure the periphery’s terms of trade in the nineteenth century because of the massive

price convergence that took place. Nevertheless, and despite his claims to the

contrary, Williamson relies heavily on such estimates: fully 12 of his 21 series should

be classified as proxy estimates, while only two are own-price price estimates.

Consequently, as shown in this chapter, Williamson has undermined his own narrat-

ive by repeating Singer’s original error. His alternative account of India’s deindustri-

alisation, for example, would have been unnecessary had its terms of trade been

measured correctly. Perhaps even China, were its own prices used, would be seen as

having a terms-of-trade boom that could explain its deindustrialisation as well.

If this conclusion is accepted, the question becomes why deindustrialisation

should have led to the periphery’s underdevelopment. Indeed, Williamson is not the

first to observe that improved terms of trade undermined cottage industries outside

the North Atlantic core, as Maurice Lévy-Leboyer before him recognised that they

had driven deindustrialisation. In stark contrast to Williamson, however, he could see

little negative in it.64 ‘One is hard put’, Lévy-Leboyer wrote, ‘to see why new nations

could not improve their level of living by specialising in primary industry. From that

point of view, deindustrialisation is desirable, on the obvious condition that the coun-

tries in question have crops which can be used by the West’.65 Lévy-Leboyer thus

begs the question: Whither Ricardo? Why would specialisation in primary-commod-

ity production for export result in underdevelopment? To answer these questions, the

following chapter examines the uneven impact of the long boom on different regions

across the periphery, in order to explain why it did, indeed, bring prosperity to some,

while also making others stagnate.

Appendix 2.1: 21 Terms-of-Trade Estimates, 1750-1913This appendix provides a survey of the sources of each of the 21 estimates used by

Williamson to measure the periphery’s terms of trade in the nineteenth century. The

results of this survey were already summarised in Table 2.2. To reiterate, the ‘net

barter terms of trade’ (NBTT) are calculated as export prices (Px) divided by import

64. Lévy-Leboyer, Banques européenes, ch. 6.65. Ibid., p. 193; quoted and translated by C. Tilly, ‘Flows of Capital and Forms of Industry in

Europe, 1500-1900’, Theory and Society, 12:2, 1983, p. 138.

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prices (Pm), so what will be described here is the methodology used to calculate Px

and Pm in each of the 21 estimates used by Williamson. For nine countries, the

calculations were predominantly done by Williamson and his co-authors, while the

remaining 12 were gathered by Williamson from the existing literature. To under-

stand how the series were calculated, it proved necessary to consult all of those

sources, as well as Williamson’s own work, giving rise to the survey presented here.66

In Table DA.2 in the Data Appendix Williamson’s series, which he kindly provided,

are reproduced.

Using the vocabulary developed in this chapter, Williamson’s database

includes just two series that can be considered own-price terms of trade, although

even one of those comes with some caveats:

1) Indonesia. For 1825-1913, both Px and Pm are chained Laspeyres indices cal-

culated from wholesale prices from Java.67

2) Japan. For 1857-1865, terms of trade (Px/Pm) interpolated between figures

for 1857, 1860, and 1865, which were apparently calculated from Japanese

price records.68 For 1866-75, Williamson used geometric interpolation. For

1876-1913, Px and Pm are chained implicit Paasche indices calculated from

unit values taken from Japan’s trade statistics. Pm is not strictly an own-price

series because prior to 1903 imports were recorded FOB and not CIF. How-

ever, considerable effort has been made by the series’ authors to adjust the

FOB figures to CIF using a freight-rate index, so they can be taken as reason-

ably accurate representations of domestic prices, although strictly speaking

the result is an adjusted part-proxy estimate during 1876-1903.69

By contrast, Williamson’s database contains fully 12 series that were predom-

66. In the accompanying footnotes, the references are to the pages in the sources where the methodo-logy is described. For a primer on the different types of index described (Fisher, Laspeyres, andPaasche), see C.H. Feinstein and M. Thomas, Making History Count: A Primer in QuantitativeMethods for Historians, Cambridge, 2002, pp. 507-25.

67. Korthals Altes, Changing Economy, XV, pp. 158-60. Also see above, pages 72-80.68. M. Miyamoto, Y. Sakudō, and Y. Yasuba, ‘Economic Development in Preindustrial Japan,

1859-1894’, Journal of Economic History, 25:4, 1965, p. 553.69. Yamazawa and Yamamoto, Estimates of Long-Term Economic Statistics, XIV, pp. 169-70, 193,

197; for the adjustments, see M. Baba and M. Tatemoto, ‘Foreign Trade and Economic Growth inJapan: 1858-1937’, in L. Klein and K. Ohkawa, eds., Economic Growth: The Japanese Experi-ence since the Meiji Era, Homewood, 1968.

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inantly calculated as proxy terms of trade (that is, calculated using prices drawn from

the core countries):

3) Argentina. For 1811-70, Px is a Paasche index; Pm is a geometric mean of

two Laspeyres indices; both were calculated using wholesale prices and unit

values drawn from several core countries.70 For 1871-85, Px is a chained

Laspeyres index calculated from British commodity prices; Pm is a re-

weighted US wholesale price index.71 For 1886-1913, Williamson gives

Blattman, Hwang, and Williamson as his source, but from his underlying

database it would appear that Px is a chained Laspeyres index originally cal-

culated by Alec Ford from a mixture of Argentine and British price series;

while Pm is a Laspeyres index calculated from British wholesale prices and

unit values.72 It should be noted that Ford’s estimates are not proxy estimates,

as they combine domestic wholesale prices for exports with adjusted proxy

prices for other exports and imports. Nonetheless, given that only the end of

the whole series used by Williamson has been calculated in this way, it is pre-

dominantly a proxy estimate. Also worth noting is that Ford’s original work

was undermined by Guido di Tella and Manuel Zymelman, when they attem-

pted to chain two of his series for Px.73 Rather than ratio splicing them, di

Tella and Zymelman simply jumped from one series to the other in 1892, res-

ulting in an artificial increase. Unfortunately, other scholars, including Willi-

amson, have tended to use the di Tella and Zymelman version, rather than

Ford’s original.74

4) Ceylon. For 1782-1913, Px is a chained Laspeyres index calculated from

British and US wholesale prices and unit values; Pm is an index of British ex-

port prices.75

70. Newland, ‘Exports and Terms of Trade’, pp. 413-15; for the underlying data, see idem, ‘Pura-mente animal: Exportaciones y crecimiento en Argentina 1810-1870’, mimeo, 1990.

71. Blattman, Hwang, and Williamson, ‘Winners and Losers’.72. A.G. Ford, ‘Export Price Indices for the Argentine Republic, 1881-1914’, Inter-American Econ-

omic Affairs, 9:2, 1955.73. di Tella and M. Zymelman, Etapas del desarrollo, p. 56, Table 10.74. For example, O.J. Ferreres, Dos siglos de economía argentina, 1810-2004: Historia argentina en

cifras, Buenos Aires, 2005, p. 658. Williamson seems to have been passed the di Tella andZymelman series from this source. See Williamson, ‘Globalization and the Great Divergence’, p.390; and L. Arroyo Abad, ‘Persistent Inequality? Trade, Factor Endowments, and Inequality inRepublican Latin America’, Economic History Review, 73:1, 2013, p. 71.

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5) China. For 1782-1913, as for Ceylon, with Indian opium wholesale prices ad-

ded to the British export prices for Pm.76

6) Cuba. For 1826-1884, Px and Pm are chained Fisher ideal indices calculated

using unadjusted unit values from British, French, and US trade statistics.77

7) India. For 1800-1913, Px is a chained Laspeyres index calculated from Brit-

ish wholesale prices and unit values, supplemented by opium wholesale

prices from India itself; Pm is a reweighted US wholesale price index.78

8) Italy. For 1817-1913, Px and Pm were calculated from British wholesale

prices and unit values; the types of indices are unclear.79

9) Malaya. For 1882-1913, Px and Pi are Laspeyres indices calculated from

British, Thai, and US wholesale prices and unit values.80

10) Mexico. For 1750-1800, silver price in Mexico for Px; Pi is an arithmetic

mean of various series of wholesale prices of textiles in Spain.81 For 1801-28,

silver price for Px; Pm is an index of British export prices.82 For 1829-76, sil-

ver for Px; Pm is a chained Laspeyres index calculated from US trade statist-

ics.83 For 1876-1913, Px is a chained Laspeyres index calculated from British

commodity prices; Pm is a reweighted US wholesale price index.84 In the

source for 1750-1828, the treatment of silver prices is unclear – it could be

that this period is a part-proxy estimate. For 1829-76, the silver price appears

to come from the United States, although again it is somewhat unclear.

11) The Philippines. For 1782-1913, Px is a chained Laspeyres index calculated

using British wholesale prices and unit values, as well as US food prices (!)

75. Williamson, ‘Globalization and the Great Divergence’, p. 391.76. Ibid., p. 391.77. L.K. Salvucci and R.J. Salvucci, ‘Cuba and the Latin American Terms of Trade: Old Theories,

New Evidence’, Journal of Interdisciplinary History, 31:2, 2000.78. Clingingsmith and Williamson, ‘Deindustrialization in 18th and 19th Century India’, pp. 231-32;

and Blattman, Hwang, and Williamson, ‘Winners and Losers’.79. Glazier, Bandera, and Berner, ‘Terms of Trade’, p. 43.80. G. Huff and G. Caggiano, ‘Globalization and Labor Market Integration in Late Nineteenth- and

Early Twentieth-Century Asia’, Research in Economic History, 25, 2008, p. 345; also see W.G.Huff, ‘Boom-or-Bust Commodities and Industrialization in Pre-World War II Malaya’, Journal ofEconomic History, 62:4, 2002, p. 1095, Table 4.

81. Dobado González, Gómez Galvarriato, and Williamson, ‘Mexican Exceptionalism’, p. 802.82. Ibid., p. 802.83. R.J. Salvucci, ‘The Origins and Progress of U.S.-Mexican Trade, 1825-1884: “Hoc opus, hic

labor est”’, Hispanic American Historical Review, 71:4, 1991, pp. 706, 730-31; and Salvucci andSalvucci, ‘Cuba and the Latin American Terms of Trade’, pp. 221-22.

84. Blattman, Hwang, and Williamson, ‘Winners and Losers’.

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as a proxy for copra; Pm is an index of British export prices.85

12) Russia. For 1782-1913, Px is a chained Laspeyres index calculated using

British and US commodity and wholesale prices; Pm is an index of British

export prices.86

13) Siam. For 1782-1913, as for Russia.

14) Venezuela. For 1830-1913, the exact sources and methodology underlying

both Px and Pi are unclear, but they appear to be based on foreign prices.87

Williamson also uses two adjusted proxy estimates, which were mainly calcu-

lated using prices from the core that have been adjusted to make them better reflect

prices in the periphery:

15) Ottoman Turkey. For 1800-54, Px is a Laspeyres index calculated using Brit-

ish CIF prices for silk and wool, US wholesale prices of tobacco and raisins,

Indian wholesale prices of opium, and Turkish wholesale prices of wheat,

with the silk, wool, and raisins prices adjusted for changes in freight rates;

Pm is an unadjusted index of British export prices.88 For 1854-1913, both Px

and Pm are annually chained Fisher ideal indices calculated from unit values

taken from Austrian, British, French, German, and US trade statistics, all ad-

justed using indices for insurance and freight rates from the United States.89

These adjustments are probably inadequate because they do not take into ac-

count other trade costs, while the US insurance and freight-rate indices may

not reflect changes in trade costs for Ottoman Turkey.

16) Spain. For 1750-1913, Px and Pm are both chained Fisher ideal indices calcu-

lated from British and Dutch wholesale prices and unit values, adjusted by in-

dices for Belgian, British, and Spanish freight and insurance rates.90 Again,

other trade costs would need to be considered to make the adjustment

85. Williamson, ‘Globalization and the Great Divergence’, p. 391.86. Ibid., p. 391.87. A. Baptista, Bases cuantitativas de la economía venezolana 1930-1995, 2nd ed., Caracas, 1997,

pp. 269-70.88. Ş. Pamuk and J.G. Williamson, ‘Ottoman De-Industrialization 1800-1913: Assessing the Magn-

itude, Impact, and Response’, Economic History Review, 64:S1, 2011, pp. 182-84.89. Pamuk, ‘Foreign Trade’, pp. 187-89, 253-76; cf. idem, Ottoman Empire, pp. 168-71.90. Prados de la Escosura, ‘Comercio hispano-británico’, pp. 121-23, 133-40; and idem, ‘Relaciones

reales de intercambio’, pp. 129-31, 151.

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correctly.

Three series used by Williamson were part-proxy estimates, in that they used

local prices for exports but unadjusted core prices for imports:

17) Brazil. Px is a Paasche index calculated using unit values from Brazil’s trade

statistics; Pm is an index of British export prices.91

18) Egypt. For 1796-1913, Px is wholesale cotton prices in Alexandria up to

1899, then US wholesale cotton prices; Pm is an index of British export

prices.92

19) The Levant. For 1839-1913, Px is an unknown type of index, apparently cal-

culated using local wholesale prices; Pm is an index of British export prices.93

Neither of Williamson’s two remaining series inspires great confidence:

20) Portugal. The series was calculated using unit values from Portugal’s trade

statistics, but comes with the major caveat that ‘[g]iven that the valuation of

exports in the official Portuguese statistics cannot be considered reliable, the

results of the export price and terms of trade indices of Portuguese foreign

trade will be presented here without any attempt to interpret them’.94

21) Chile. For 1810-1913, both Px and Pm were collated by Oscar Braun and his

co-authors from a variety of secondary sources.95 For 1810-44, Braun et al

used a consumer-price index from Lima (!) for Px; Pm is British export

prices. For 1845-61, a part-proxy estimate is used, as Px is calculated using

unit values from Chile’s trade statistics; Pm is an index of British export

prices.96 For 1862-1900, both Px and Pm are Paasche indices calculated using

91. N.H. Leff, Underdevelopment and Development in Brazil, I, London, 1982, p. 82, Table 5.2.92. Pamuk and Williamson, ‘Ottoman De-Industrialization, 1800-1913’, p. 35.93. C. Issawi, The Fertile Crescent, 1800-1914: A Documentary Economic History, New York and

Oxford, 1988, pp. 147-49.94. P. Lains, ‘Exportações portuguesas, 1850-1913: A tese da dependência revisitada’, Análise

Social, 22:91, 1986, p. 388, author’s translation.95. Compiled by J. Braun, M. Braun, I. Briones, J. Díaz, R. Lüders, and G. Wagner, ‘Economía

chilena 1810-1995: Estadísticas históricas’, Documento de Trabajo 187, Instituto de Economía,Pontificia Universidad Católica de Chile, 2000, pp. 93-94.

96. Both from J.G. Palma, ‘Growth and Structure of Chilean Manufacturing Industry from1930-1935: Origins and Development of a Process of Industrialization in an Export Economy’,

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unit values from Chile’s trade statistics.97 For 1900-13, the sources are un-

known as there is no series for Chile’s terms of trade in the reference given by

Braun et al.98 It should be noted that the use of Chile’s trade statistics for im-

port unit values is dubious because they were based on fixed ‘tariff values’.99

Taken as a whole, then, Braun et al’s series is problematic.

Appendix 2.2: India’s Terms of Trade, 1861-1913The new own-price estimate of India’s terms of trade used in Figures 2.4 and 2.10

was calculated from 50 wholesale price series published by the British authorities.100

Previously those prices were used by the British authorities to calculate export and

import price indices as crude unweighted, arithmetic means.101 Here, by contrast,

export and import price indices have been calculated by chaining various geometric

Laspeyres indices. Coverage is 80-90 percent of the value of exports and 50-60

percent of imports, and is broadly representative of coastal India.102 The indices are

reproduced in Table DA.5 in the Data Appendix.

To calculate the new indices, trade statistics were used to assign weights to

the different price series for 1860, 1870, 1880, et cetera, as shown in Tables A2.1 and

A2.2. Geometric Laspeyres indices were then calculated for 10 years either side of

the base year, so, for example, a series was calculated for 1860-80, using weights--

PhD diss., Oxford University, 1979, p. 76, fn. 1, and Appendices 5, 6, 7, 16, and 18.97. From C. Clavel, ‘Los términos de intercambio en el largo plazo, 1860-1900’, paper presented at

the Encuentro Anual de Economistas de Chile, 1990, pp. 5-10.98. ECLA, Economic Survey of Latin America 1949, New York, 1951, p. 17, Table 2A.99. A. Llona, ‘On the Accuracy of Chilean Foreign Trade Statistics During the Nitrate Boom:

1870-1935’, paper presented at the Conference on Trade, Poverty and Growth in History,Fundación Ramón Areces, Madrid, 17-18 May 2012, pp. 10-11, available online at http://www.uc3m.es/portal/page/portal/instituto_figuerola/home/research/poverty_growth2012/parti-cipants/A.LL.pdf (accessed 10 May 2013).

100. Some grain prices were retail, as indicated below. All but one of the series is from DCIS, IndexNumbers, pp. 10-15, Table 6. The exception is opium, which for 1861-97 is from DFC, Financialand Commercial Statistics for British India, 6, 1899, p. 57, Table 4; and for 1898-1913, fromvarious issues of East India Office, Statistical Abstract Relating to British India, through theDigital South Asia Library, online at http://dsal.uchicago.edu/statistics (accessed 1-5 November2012).

101. DCIS, Index Numbers, p. 1, Table 1. The series are reproduced in M. McAlpin, ‘Price Move-ments and Fluctuations in Economic Activity (1860-1947)’, in D. Dumar and M. Desai, eds., TheCambridge Economic History of India, II, c. 1757-c. 1970, Cambridge, 1983, pp. 903-04,Appendix Table 11A.1.

102. The British collected the prices from various coastal cities. Fortunately, when two or more seriesare available for different places, they are similar, which suggests that the terms of trade calcu-lated here can be taken as broadly representative of coastal India as a whole.

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Table A2.1Weights in India’s Import Price Index

1860 1870 1880 1890 1900 1910 1920

Coal (1865+) .0219 .0195 .0354 .0343 .0068 .0075 .0018Copper .0789 .0568 .0462 .0403 .0204 .0472 .0158Cotton manufactures .6783 .6547 .6537 .6049 .6075 .5432 .5289Cotton, yarn .1274 .1401 .1055 .0837 .0553 .0409 .0811Iron .0331 .0334 .0442 .0569 .0698 .1230 .1869Mineral oil (1888+) .0148 .0585 .0768 .0439 .0498Salt (1862+) .0222 .0299 .0190 .0173 .0126 .0091 .0136Silk, raw .0295 .0374 .0304 .0248 .0226 .0111 .0097Spelter .0088 .0051 .0048 .0039 .0027 .0025 .0017Sugar (1870+) .0232 .0460 .0755 .1256 .1716 .1105

Note: The years are official rather than calendar years, so 1860 equals April 1860 to March1861. The totals may not equal 1 due to rounding.

Sources: 1860-1910: calculated from East India Office, Statistical Abstract, various years,through the Digital South Asia Library; and ibid. 1929, pp. 462-65, Table 207.

from 1870.103 Geometric means of all the overlapping periods were then calculated

and linked through ratio splicing.104

The following are notes for specific import prices:

1) Cotton manufactures. This was by far the most important import category.

Here it is represented by grey shirtings, which accounted for 18 percent of

total imports of cotton manufactures during 1908-12.105 The representative-

ness of the evolution of the price series was verified against trade statistics for

the early 1870s and the 1910s.

2) Cotton yarn. Geometric mean of two series, one for grey and another for col-

oured yarn.

3) Mineral oil. A series for kerosene, which represented 76 percent of mineral

oil imports during 1908-12.106

103. A chained geometric Laspeyres index was used because it is a shorthand means to approximate achained Fisher index. See IMF, Producer Price Index: Theory and Practice, Washington, DC,2004, pp. 566, 593.

104. The geometric mean was preferred for splicing due to its mathematical properties. See R.J. Hilland K.J. Fox, ‘Splicing Index Numbers’, Journal of Business & Economic Statistics, 15:3, 1997,pp. 387-89.

105. Calculated from East India Office, Tables Relating to the Trade of British India with BritishPossessions and Foreign Countries 1908-09-1912-13, London, 1914, p. 38, Table 8.

106. Ibid., p. 35, Table 8.

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Table A2.2Weights in India’s Export Price Index

1860 1870 1880 1890 1900 1910 1920Coal (1889+) .0000 .0003 .0066 .0044 .0075

Cotton piece goods (1874+) .0051 .0089 .0130 .0160 .0126 .0406Cotton, raw .2547 .3874 .2016 .1910 .1132 .2063 .2091

Cotton, yarn (1874+) .0013 .0195 .0757 .0466 .0493 .0510Ghee (1871+) .0006 .0010 .0010 .0021 .0016 .0025Grains

Barley .0001 .0000 .0001 .0001 .0001 .0006 .0007

Gram .0024 .0009 .0015 .0012 .0011 .0020 .0006Jawar and bajra .0050 .0018 .0032 .0041 .0006 .0011 .0012Rice .1028 .0837 .1379 .1490 .1477 .1329 .0913Wheat .0047 .0021 .0499 .0699 .0003 .0741 .0206

Hides, raw (1867+) .0167 .0292 .0286 .0196 .0589 .0309 .0108Indigo .0654 .0635 .0544 .0356 .0239 .0019 .0021Jute manufactures .0317 .0069 .0172 .0287 .0876 .0972 .2659Jute, raw .0142 .0513 .0599 .0880 .1215 .0886 .0821Lac .0060 .0027 .0086 .0090 .0119 .0123 .0380Opium .3533 .2147 .2071 .1072 .1057 .0730 .0127Saltpetre .0230 .0088 .0054 .0044 .0038 .0021 .0036Seeds

Linseed .0123 .0337 .0563 .0577 .0498 .0480 .0273Poppy .0001 .0021 .0061 .0055 .0077 .0051 .0029Rape .0076 .0208 .0102 .0113 .0138 .0266 .0152

Sesamum or til .0007 .0093 .0200 .0157 .0174 .0183 .0104Silk, raw .0360 .0251 .0083 .0060 .0057 .0029 .0017Skins, dressed

Goat (1866+) .0020 .0035 .0109 .0134 .0192 .0092 .0032Sheep (1866+) .0015 .0026 .0080 .0099 .0141 .0067 .0024

SugarRefined .0007 .0002 .0003 .0004 .0003 .0002 .0011Unrefined (1867+) .0358 .0046 .0044 .0044 .0016 .0007 .0037

Tea (1871+) .0223 .0465 .0604 .1067 .0710 .0610Vegetable oil .0069 .0028 .0084 .0061 .0059 .0041 .0145Wool, raw .0166 .0132 .0154 .0112 .0101 .0162 .0163

Note: The years are official rather than calendar years, so 1860 equals April 1860 to March1861. The totals may not equal one due to rounding.

Sources: Calculated from data compiled from Board of Trade, Statistical Tables Relating tothe Colonial and Other Possessions of the United Kingdom, 8, 1863, pp. 47, 51-61, Tables 50,54 and 55; East India Office, Tables Relating to the Trade of British India, various years; andthe sources given in Table A2.1.

In the case of export prices, in some years it was necessary to estimate

weights based on the participation of a good in a more aggregated category in other

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years. For instance, in 1870 the value for ghee exports was unavailable, so it was

estimated as follows: in 1880 ghee was 25.9 percent of the provisions category; in

1870 provisions exports were £115,632; so ghee exports were estimated at £29,984

(that is, 115,632 multiplied by 0.259). These are notes for specific export prices:

1) Barley. Retail prices.

2) Cotton piece goods. Represented by T. cloths, which accounted for 43 percent

of cotton piece good exports in 1912.107

3) Gram. Retail prices.

4) Jawar and bajra. Geometric mean of two retail prices series, one for jawar, the

other for bajra.

5) Jute manufactures. Represented by gunny bags, which accounted for 48 per-

cent of exports of jute manufactures during 1908-12.108

6) Jute, raw. Geometric mean of two series, ordinary and picked, both from

Calcutta.

7) Lac. Represented by the geometric mean of first and second orange shell lac.

Shell lac accounted for 88 percent of lac exports during 1908-12.109

8) Linseed. Geometric mean of two series, one from Calcutta, the other from

Bombay.

9) Rice. Geometric mean of two series, Moonghy and Ballam (both from Cal-

cutta). For Moonghy, the figures were interpolated based on the evolution of

Ballam in 1907 and 1909.

10) Tea. Geometric mean of three series: Peokoe, Souchong, and Congou, all

from Calcutta.

11) Vegetable oils. Represented by castor oil, which accounted for just 23 percent

of total vegetable oil exports during 1908-12.110 Nevertheless, castor oil was

given the weight of all vegetable oils in order to better represent the import-

ance of this type of good in India’s exports.

12) Wheat: Geometric mean of three series when they overlap: Club No. 2 (Cal-

cutta) for 1861-1913, Khandwa (Bombay) for 1867-1913, and Delhi No. 1

107. Ibid., p. 52, Table 10.108. Ibid., p. 53, Table 10.109. Ibid., p. 48, Table 10.110. Ibid., p. 50, Table 10.

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(Bombay) for 1871-1913.

13) Wool: Geometric mean of two series when they overlap, one from Bombay

for 1861-1913 and the other from Karachi for 1870-1913.

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Chapter 3

A New Order

The bourgeoisie, by the rapid improvement of all instruments of production, by theimmensely facilitated means of communication, draws all nations, even the mostbarbarian, into civilization. The cheap prices of its commodities are the heavy artil-lery with which it batters down all Chinese walls, with which it forces barbarians’intensely obstinate hatred of foreigners to capitulate.

Karl Marx and Friedrich Engels, Manifesto of the Communist Party1

The periphery’s long terms-of-trade boom drove global divergence through its radic-

ally different effects on land-abundant and land-scare regions. Where land was

abundant, frontiers could expand, allowing the European offshoots in Australasia and

North America to prosper. In the land-scarce periphery, by contrast, deindustrialisa-

tion led to stagnation. The result was what Andre Gunder Frank called the ‘develop-

ment of underdevelopment’,2 with progress and decline occurring as parts of the

same process. Where this chapter goes beyond Frank is in arguing against many of

the assumptions that he and others inherited from Latin American structuralism,

according to which an improvement in the terms of trade should be conducive to the

periphery’s development.3 Rather, this chapter contends, it was a terms-of-trade

1. K. Marx and F. Engels, Manifesto of the Communist Party, New York, (1848) 1948, p. 13.2. Frank, Latin America, ch. 1, esp. p. 4.3. Frank is often, arguably incorrectly, classified as a dependentista (see C. Kay, ‘André Gunder

Frank: From the ‘Development of Underdevelopment’ to the ‘World System’’, Development andChange, 36:6, 2005, pp. 1180-81), while ‘dependency theory’ is often amalgamated with Preb-isch-inspired ‘structuralism’. A failure to discover a deterioration in the terms-of-trade is thentaken as a refutation of Frank and other dependentistas. For example, J. Schneider, ‘Terms ofTrade between France and Latin America, 1826-1856: Causes of Increasing Economic Disparit-ies?’, in P. Bairoch and M. Lévy-Leboyer, eds., Disparities in Economic Development since theIndustrial Revolution, London, 1981, pp. 116-17; Prados de la Escosura, ‘Relaciones reales’, p.147; Haber, ‘Introduction: Economic Growth’, pp. 9, 12; and Coatsworth, ‘Structures, Endow-ments’, p. 134. Frank himself, however, was scathing about the structuralists’ fixation with theterms of trade. Frank, Latin America, pp. 405-06. Moreover, the terms of trade also featured little,if at all, in his own forays into global history. For example, idem, Dependent Accumulation andUnderdevelopment, London, 1978, esp. pp. 101-03; idem, World Accumulation, 1492-1789, NewYork, 1978; and idem, ReOrient: Global Economy.

- 96 -

boom that drove divergence during the long nineteenth century, as it divided the

world into an industrialised North Atlantic core, the prosperous European offshoots,

and an ‘overpopulated’ poor periphery.

This chapter provides a new framework for understanding the nineteenth

century’s great divergence(s). It begins by discussing how the long boom allowed

land-abundant countries to prosper, refuting Jeffrey Williamson’s claim that

improved terms of trade resulted in a ‘resource curse’ that impeded growth.4 Indeed,

where land was abundant the expanding frontier could generate a safety-valve effect

on labour markets, keeping wages high. The result was rapid intensive (that is, per

capita) growth based on heavy investment in labour-saving machinery, as John

Habakkuk famously argued.5 This chapter illustrates these processes with the archet-

ypal case of the United States, then discusses how they also occurred, to varying

degrees, in other land-abundant countries. Subsequently, it explores the bifurcation

between the land-scarce North Atlantic core and the similarly land-scarce regions of

the poor periphery. Following the historiographical debate about the relationship

between overseas trade and Britain’s industrial revolution,6 it describes how the

industrialisation of the core caused and required the periphery’s deindustrialisation,

resulting in the Arthur Lewis-style world of increasing quantities of labour receiving

diminishing returns by being applied to a more or less fixed amount of land.7 In this

way, the chapter answers Maurice Lévy-Leboyer’s question of why deindustrialisa-

tion should have led to underdevelopment.8 Chapter 4 will then apply this new

metanarrative of global divergence to the Argentine case.

Land and GrowthData on land resources and estimates of historical populations can be used to identify

4. Williamson, Trade and Poverty, pp. 50-51, 183-84.5. Habakkuk, American and British Technology, esp. ch. 3; cf. von Nardroff, ‘American Frontier’,

pp. 138-39.6. For an overview of the debate, see R. Findlay and K.H. O’Rourke, Power and Plenty: Trade,

War, and the World Economy in the Second Millennium, Princeton, 2007, pp. 330-45, 358-64.The most important works drawn upon in this chapter are P.K. O’Brien and S.L. Engerman,‘Exports and the Growth of the British Economy from the Glorious Revolution to the Peace ofAmiens’, in B. Solow, ed., Slavery and the Rise of the Atlantic System, Cambridge, 1991, pp.177-209; Cuenca Esteban, ‘Rising Share’; and R.C. Allen, The British Industrial Revolution inGlobal Perspective, Cambridge, 2009, esp. pp. 16-22.

7. Lewis, ‘Economic Development’, pp. 140-55.8. Lévy-Leboyer, Banques européenes, p. 193; also see Chapter 2, page 85.

- 97 -

the land-abundant regions of the world at the beginning of the long nineteenth

century. In the first column of Table 3.1 each region’s arable potential is indicated by

the amount of land that could potentially be used for rain-fed arable agriculture;9 in

the second column that quantity of potential arable land has been divided by the

region’s population in 1780, in order to give an idea of how abundant land was relat-

ive to labour; in the third and fourth columns, the extent to which that arable poten-

tial was realised is measured by showing the amount of cropland in 1780 and 1910 as

a percentage of the potential amount of arable land. Given limitations in the data, the

results must be treated as approximate, but the general picture is likely to be

correct.10 It suggests that the land-abundant regions – in other words, the places

where potential arable land per capita was high – were Oceania, North America, and

South America, with Southern Africa trailing by some distance, and with little arable

potential in the great Eurasian land mass.

The populations of the land-abundant regions tended to grow the fastest

during the nineteenth century, as can be seen in Figure 3.1. Using a sample of 104

countries across four centuries, it can be seen that the availability of land became

strongly correlated with whether a country’s population expanded or stagnated. On

the vertical axis of each panel is the growth in population across the century, while

on the horizontal axis is an indicator of the potential arable land per capita at the

beginning of each century. During the sixteenth and seventeenth centuries there was

no correlation between land and growth, as the populations of the land-abundant

countries grew no faster than the land-scarce countries. In the eighteenth century the

future United States did begin to grow rapidly, aided by the import of African

slaves,11 as in Haiti, a land-scarce country that also grew at a fast pace thanks to the

9. This is estimated by the Food and Agriculture Organization (FAO) using maps of the world’sclimates and soils, combined with a database of the needs of 21 of the world’s major crops. Theresult includes land that is currently under cultivation for rain-fed agriculture and land that couldpotentially be brought into cultivation. It does not include irrigated land. See A.J. Bort, F.O.Nachtergaele, and A. Young, ‘Land Resource Potential and Constraints at Regional and CountryLevels, 2000’, World Soil Resources Report 90, FAO, 2000, pp. 37-38.

10. On problems with historical population estimates, see Platt, Mickey Mouse Numbers, pp. 20-23,34-35; and Austin, ‘Reversal of Fortune’, pp. 1001-03. For croplands, the History Database of theGlobal Environment (HYDE) of the Netherlands Environmental Assessment Agency has beenpreferred to the Global Land Use Database of the Center for Sustainability and the Global Envir-onment (SAGE) because the HYDE figures seem more reliable. See Appendix 3.1 for furtherdetails.

11. D.W. Galenson, ‘The Settlement and Growth of the Colonies: Population, Labor, and EconomicDevelopment’, in S.L. Engerman and R.E. Gallman, eds., The Cambridge Economic History of

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Table 3.1Global Arable Potential, 1780-1910

Arable potential* Potential used (%)**

Millionkm2

Ha percapita in

17801780 1910

Americas 15.1 66 1 15North 4.8 93 1 41Central and Caribbean 0.8 9 5 16South 9.5 110 1 2

Africa 11.4 14 4 7North 0.3 3 14 40West 5.5 11 6 8East 2.0 12 3 9Southern 3.6 39 1 3

Asia 7.1 1 28 45Western 0.5 2 50 65Central 0.2 3 34 83East 2.2 1 38 47South 2.3 1 33 61Southeast 1.9 6 4 17

Europe 6.3 4 21 46Northern and central 1.7 2 27 45Eastern 3.7 11 15 45Southern 0.9 2 33 51

Oceania 1.3 247 0 8

* Land that could be used for rain-fed arable agriculture.

** Total cropland in cultivation as a percentage of arable potential.

Note: The figures are calculated from the database of 166 countries contained in Table DA.9in the Data Appendix.

Sources:

Arable potential: Bort, Nachtergaele, and Young, ‘Land Resource Potential’, pp. 101-10,Table A8.

Croplands and population: data described in K.K. Goldewijk, A. Beusen, G. van Drecht, andM. de Vos, ‘The HYDE 3.1 Spatially Explicit Database of Human-Induced Global Land-UseChange Over the Past 12,000 Years’, Global Ecology and Biogeography, 20:1, 2011, pp. 73–86; data available online at ftp://ftp.pbl.nl/../hyde/supplementary/land_use/his_crop.xls andftp://ftp.pbl.nl/../hyde/tmp/hispop_2008Rev.xls (accessed 5 September 2013).

For the underlying dataset, see Table DA.9 in the Data Appendix.

the United States, I, The Colonial Era, Cambridge, 1996, pp. 169-75

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construction of an irrigation system by French engineers and slave labour.12 In the

nineteenth century the other land-abundant countries – especially Australia, Argen-

tina, Brazil, and Canada, but arguably also South Africa13 – became the fastest-grow-

ing countries in the world due to massive inflows of European settlers. As can be

seen in Figure 3.1, it was only at this point that a positive correlation between land

and growth began. Until then, the coefficients of determination indicate that land

played little or no role as a determinant of population growth. In the nineteenth

century, by contrast, two thirds of the variation in population growth among these

104 countries became determined by their potential arable land per capita.14 This was

because the other land-abundant countries had begun to follow the path first taken by

the United States.

The United StatesThe United States was the first land-abundant country to begin growing rapidly.

From just a quarter of a million people in 1700, the American colonies had expanded

to contain 2.8 million by 1780.15 This population growth was particularly impressive

because it did not depress living standards. Indeed, the recent research of Robert

Allen and his associates has suggested that the American colonists’ living standards

improved during the eighteenth century.16 They have arrived at this finding through

12. It should be remembered that the potential arable land in Figure 3.1 only includes land suitablefor rain-fed agriculture. On Haiti, see R. Blackburn, The Making of New World Slavery: From theBaroque to the Modern 1492-1800, London, 1997, pp. 434-35, 441-42.

13. South Africa can be considered an artificially land-abundant country, as the African peasantry’sland was appropriated for the benefit of European settlers. See C. Bundy, ‘The Emergence andDecline of a South African Peasantry’, African Affairs, 71:285, 1972.

14. In Figure 3.1 the full 166-country database contained in Table DA.9 in the Data Appendix hasbeen reduced to 104 countries, with all those with a population of less than one million in 1900excluded. With all 166 included, the R2 equals 0.00 for the seventeenth and eighteenth centuries,0.14 for the eighteenth, and 0.76 for the nineteenth. This high R2 for the nineteenth century is,however, due to the phenomenally high growth of the Gambia, a minute land-abundant Britishcolony that grew dramatically. With the Gambia excluded, the R2 falls to just 0.11. That is,however, largely due to the influence of French Guiana, a small land-abundant French colonythat grew little, and Hong Kong, the British city-colony that grew from just 18,000 people in1800 to 306,000 in 1900. With these two countries excluded, the R2 goes back up to 0.46.Excluding or including a variety of other minor countries has similar effects, so here they are allexcluded to focus the analysis on the more important cases, with a population of one million in1900 set as an arbitrary cutoff.

15. These figures are for the American colonies, excluding Canada and the Indians. Bureau of theCensus, Historical Statistics of the United States: Colonial Times to the 1970, II, Washington,DC, 1975, p. 1168, Series Z1. The estimates used in Figure 3.1 are different because they are forthe whole of today’s United States.

16. R.C. Allen, T.E. Murphy, and E.B. Schneider, ‘The Colonial Origins of the Divergence in the

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Figure 3.1Arable Potential and Population Growth, 1500-1900

-500

0

500

1000

1500

2000

0 100 200 300 400 500 600 700

Arable potential**

Pop

ulat

ion

grow

th* (a) 16th century

R2 = 0.00 -500

0

500

1000

1500

2000

0 100 200 300 400 500 600 700

(b) 17th century

R2 = 0.00

-500

0

500

1000

1500

2000

0 100 200 300 400 500 600 700

(c) 18th century

Haiti USA

Canada Brazil

Australia Argentina R2 = 0.12

-500

0

500

1000

1500

2000

0 100 200 300 400 500 600 700

R2 = 0.67

(d) 19th century Argentina

Australia

USA

South Africa

Canada Brazil

* Percent population growth from beginning to end of the century.

** Hectares of land suitable for rain-fed agriculture, divided by population at the beginning ofthe century.

Note: For each century, the sample includes the same 104 countries, based on their earlyboundaries in the early twentieth-first century. The sample includes all countries included inthe dataset in Table DA.10 that had a population of at least one million in 1900.

Sources: As in Table 3.1. For the underlying data, see Table DA.10 in the Data Appendix.

the calculation of ‘welfare ratios’, which, in Allen’s words, give a rough indication of

how far people were from the ‘line between respectability and destitution’.17 The

ratios are calculated by dividing the wages of a labourer by the cost of a basket of

goods sufficient for his family’s subsistence, with a ratio of one indicating a subsist-

ence-level standard of living. Hence, welfare ratios provides an indication of how far

unskilled workers were from subsistence, with a higher ratio implying better living

Americas: A Labor Market Approach’, Journal of Economic History, 72:4, 2012.17. R.C. Allen, ‘The Great Divergence in European Wages and Prices from the Middle Ages to the

First World War’, Explorations in Economic History, 38:4, 2001, p. 426.

- 101 -

standards. How reliable the welfare ratios are depends heavily upon how much care

has been taken with an often fragmentary record of wages and prices.18 Nevertheless,

they are preferable to the highly dubious historical estimates of GDP that are

commonly used.19 Reproduced in Table 3.2, the welfare ratios calculated by Allen

and his associates suggest that free labourers in the British American colonies

enjoyed living standards similar to those of Northern Europe during the first half of

the eighteenth century, and probably overtook them during the second half.20

Looking back from the end of the eighteenth century, Adam Smith argued

that the American colonies had been able to prosper in large part thanks to a benevol-

ent British trade policy. There were ‘no colonies of which the progress has been more

rapid’, Smith wrote, ‘than that of the English in North America’.21 Comparing them

to the colonies of France, Portugal, and Spain, he contended that the British Amer-

ican colonies had been unusually blessed by the mother country’s policies, which

‘had been more favourable to the improvement of and cultivation of this land, than

those of any of the other three nations’.22 Partly this was due to legal institutions that

18. In the case of Allen’s own figures, it is possible that his welfare ratios for India are too low. S.Sivramkrishna, ‘Ascertaining Living Standards in Erstwhile Mysore, Southern India, from Fran-cis Buchanan’s Journey of 1800–01: An Empirical Contribution to the Great Divergence Debate’,Journal of the Economic and Social History of the Orient, 52, 2009; and P. Parthasarathi, WhyEurope Grew Rich and Asia Did Not: Global Economic Divergence, 1600–1850, Cambridge,2011, pp. 45-46. Malanima has also suggested there may be some problems with the data forLondon and Italy. P. Malanima, ‘When Did England Overtake Italy? Medieval and Early ModernDivergence in Prices and Wages’, European Review of Economic History, 17:1, 2013. Far moreproblematic, however, is a recent estimate of welfare ratios in Buenos Aires in the late colonialera that has sought to replicate Allen’s methodology, arriving at the conclusion that they were farhigher than in Britain at the end of the long nineteenth century. L. Arroyo Abad, E. Davies andJ.L. van Zenden, ‘Between Conquest and Independence: Real Wages and Demographic Changein Spanish America, 1530-1820’, Explorations in Economic History, 49:2, 2012, p. 157, Table 5;and Figure 3.6 below. This is, however, due to two basic errors. Specifically, Arroyo Abad et alhave used Coatsworth’s erroneously reported version of Johnson’s wage series for the years1775-95 (see Appendix 1.1, page 53, footnote 145), together with a highly dubious method ofestimating meat prices for 1775-1800: they divide the price of a cow by 207, which they assumeto be the kilos of beef on each animal. To see how clearly bogus such a methodology is, it can beapplied to Garavaglia’s cattle price series for 1810, which is when Barba’s series for retail beefprices, used by Arroyo Abad et al, begins. Garavaglia found that in that year a cow sold for 11pesos, which, divided by 207, suggests a beef price $0.05 per kilo. Barba, nevertheless, foundthat beef was selling for $1 per kilo, which gives an indication of just how much Arroyo Abad etal have underestimated beef prices. Calculated from Garavaglia, ‘Precios de los productos’, p.102, Cuadro 1; and F.E. Barba, Aproximación al estudio de los precios y salarios en Buenos Airesdesde fines del siglo XVIII hasta 1860, La Plata, 1999.

19. For the case of Argentina’s historical GDP estimates, see Appendix 1.1.20. This impression is reinforced using a different methodology by A. Hanson Jones, ‘Wealth Estim-

ates for the American Middle Colonies, 1774’, Economic Development and Cultural Change,18:4, 1970, pp. 129-32.

21. Smith, Inquiry into the Nature, II, p. 73.22. Ibid., II, p. 73.

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Table 3.2Welfare Ratios of Unskilled Labourers Around the World, 1500-1849

1500-49 1550-99 1600-49 1650-99 1700-49 1750-99 1800-49

North AmericaBoston 1.4 2.3 3.0 4.2Philadelphia 4.8 5.4Maryland 3.7 3.4 4.2

Latin AmericaBogota 1.3 2.1 2.2 2.1Mexico - urban 2.5 2.3 1.5Mexico - rural 0.2 0.6 0.9 1.3 1.5 1.4 0.9Potosí 1.8 1.8 1.8 1.7

AsiaBeijing 1.3 1.0 0.8Lower Yangtze 0.8 2.2 1.8 1.2 0.8Bengal 1.4 0.8 0.8Delhi 3.0 3.0 1.3

Northern EuropeAmsterdam 3.8 3.6 3.8 4.3 4.2 3.8 2.9Antwerp 2.9 2.9 3.0 2.5 2.8 2.5 2.3London 3.7 3.0 2.8 3.5 4.2 3.5 3.8South England towns 2.9 2.2 1.7 2.0 2.8 2.5 3.2

Central EuropeLeipzig 1.3 1.2 2.3 1.9 1.5 1.7Vienna 3.6 2.1 1.9 2.2 2.0 1.4 0.7

Southern EuropeFlorence 2.3 1.9 2.1Milan 2.6 2.5 1.4 1.0 0.7Naples 2.6 1.8 2.4 3.0 2.2 1.3 0.9Madrid 1.5 1.4 1.2 1.1Valencia 2.3 1.6 1.6 1.4 1.4 1.0

Source: Allen, Murphy, and Schneider, ‘Colonial Origins’, online appendices, pp. 29-31,Appendix Tables 2-4. The figures for central and southern Europe in Appendix Table 4 of thissource appear to be errors because the figures are identical for three pairs of cities (Valenciaand Naples, Madrid and Leipzig, Florence and Vienna). The welfare ratios for all central andsouthern European cities were on that account re-estimated by dividing the wages given inAppendix Table 2 by the cost of the subsistence baskets given in Appendix Table 3.

prevented the formation of great estates by obliging landowners to make improve-

ments to land and by limiting primogeniture.23 Furthermore, Britain had also tended

to subsidise its colonies, whereas the other empires had been more extractive.24 More

23. Ibid., II, pp. 73-75.24. Ibid., II, pp. 75-76.

- 103 -

important for Smith, however, was the relatively free trade that the British American

colonies had enjoyed. While most European states imposed strict trade monopolies

on their empires, Smith believed that the British gave their American colonies more

liberty to trade with whom they pleased.25 Consequently, merchants’ commercial

margins were squeezed, so the colonists enjoyed far better terms of trade. Smith

wrote:

[T]he number and dispersed situation of the different traders renders it impossiblefor them to enter into any general combination, and their competition is sufficient tohinder them from making very exorbitant profits. Under so liberal a policy thecolonies are enabled both to sell their own produce and to buy the goods of Europeat a reasonable price. [...] The profits of the trade, therefore, [...] though no doubtsomewhat higher than if the competition was free to all other nations, are, however,by no means exorbitant; and the price of European goods accordingly is not extra-vagantly high in the greater part of the colonies [...].26

Britain had to ensure its American colonies received better terms of trade

because Britons had to be provided with the necessary incentives to emigrate there,

given the high living standards they enjoyed at home.27 For this reason, British policy

encouraged competition among merchants, which compelled them to innovate to

reduce costs. Better packaging, in particular, reduced freight rates for tobacco, the

colonies’ principal export.28 A rough illustration of how the terms of trade then

improved is given in Figure 3.2. Unfortunately, the own-price series, shown in the

thick line in Figure 3.2, only begins in 1790, and there are insufficient price data to

extend it further back.29 Nevertheless, the thin line gives a rough indication of the

extent to which the terms of trade improved in the eighteenth century by showing the

25. Ibid., II, pp. 77-88. For conformation of this, see E.J. Hamilton, ‘The Role of Monopoly in theOverseas Expansion and Colonial Trade of Europe Before 1800’, American Economic Review,38:2, 1948.

26. Smith, Inquiry into the Nature, II, p. 78.27. Cf. Allen, Murphy, and Schneider, ‘Colonial Origins’, pp. 879-81.28. What evidence there is (for rice and tobacco exports) suggests that trade costs fell. See R.R.

Menard, ‘Transport Costs and Long-Range Trade, 1300-1800: Was There a European ‘TransportRevolution’ in the Early Modern Era?’, in J.D. Tracy, ed., The Political Economy of MerchantEmpires, Cambridge, 1991, pp. 253-64, 267-69; also J.F. Shepherd and G.M. Walton, Shipping,Maritime Trade, and the Economic Development of Colonial North America, Cambridge, 1972,ch. 4.

29. For the construction of the underlying series, see M. Simon, ‘The United States Balance ofPayments, 1861–1900’, in Conference on Research in Income and Wealth, Trends in the Amer-ican Economy in the Nineteenth Century, Princeton, 1960, pp. 647-49; D.C. North, The Econ-omic Growth of the United States, 1790–1860, Englewood Cliffs, 1961, Appendix 1; and R.E.Lipsey, Price and Quantity Trends in the Foreign Trade of the United States, Princeton, 1963,Appendix A.

- 104 -

Figure 3.2US Terms of Trade, 1659-1913

0

20

40

60

80

100

120

1650 1675 1700 1725 1750 1775 1800 1825 1850 1875 1900 1925

Terms of trade

Upper South: Tobacco/Manufactures*

1913 = 100

* Wholesale price of tobacco relative to the probate prices of manufactured goods (an indexof cloth and metals) for Virginia during 1659-1776 and Maryland during 1770-1820. During1770-76, the geometric mean of the two series was used. The entire series was thenreferenced so that 1790-1810 equals 62.79, which is the average value of the own-priceestimate of the US terms of trade during this period.

Sources:

Terms of trade: D.A. Irwin, ‘Exports and Imports of Merchandise – Price Indexes and Termsof Trade: 1790-2002’, in Carter et al, Historical Statistics, Series Ee433, Ee436, and Ee439.

Upper South manufactures prices: P.M.G. Harris, ‘Inflation and Deflation in Early America,1634-1860: Patterns of Change in the British American Economy’, Social Science History,20:4, 1996, pp. 489-94, Table A1.

Upper South tobacco prices: J.J. McCusker, ‘Wholesale Tobacco Prices in Virginia andMaryland, by Region: 1647–1820’, in Cartel et al, eds., Historical Statistics, Series Eg282and Eg283.

wholesale price of tobacco relative to the prices of manufactured goods, as recorded

in probate inventories in Maryland and Virginia. This suggests that the United States’

terms-of-trade boom began in the eighteenth century,30 probably before the long

boom started in most of the periphery.31 It encouraged Britons to emigrate to the

colonies by allowing land further from the ports (and, later, from the railway

30. For further evidence that supports this impression, see M. Egnal, New World Economies: TheGrowth of the Thirteen Colonies, New York, 1998, pp. 11-12, 63-67.

31. Cf. O’Rourke and Williamson, ‘When Did Globalisation Begin?’.

- 105 -

stations) to be profitably brought into production, since the prices of the settlers’

staple commodities were mainly set by the export prices received at the port, and the

prices of the manufactured goods that they bought were largely set by imports.

The British colonies’ improving terms of trade triggered the kind of extensive

growth predicted by staple theory,32 as periods of rising export prices saw the frontier

expand, drawing in new settlers.33 In the eighteenth century westward expansion

became the central process shaping the future United States, as the movement of

settlers out from the eastern seaboard provoked a series of conflicts involving the

colonies, the Indians, Britain, France, and Spain, which ultimately culminated in the

American Revolution and War of Independence during 1775-83. The question of the

terms of trade would be one of the major issues that provoked revolution, as the Brit-

ish government had sought to tighten its trade monopoly in the Americas to increase

the revenues that it required to service its war debts, while also placing new restric-

tions on settlement in the West to ensure that its merchant-creditors could continue to

profit from the fur trade with the Indians.34

Once independence was attained, westward expansion would become the

basis for the consensus required for the United States’ nascent democracy to func-

tion. During the era of democratisation from the mid-1830s through to the

mid-1850s, not only southern planters and yeoman farmers but also eastern labourers

and artisans came to believe in the new nation’s ‘manifest destiny’ of expansion

toward the Pacific and the Rio Grande because all stood to gain from the expanding

frontier.35 Subsequently, the conterminous United States increased its territory from

32. Cf. North, Economic Growth; and J.J. McCusker and R.R. Menard, The Economy of BritishAmerica, 1607-1789, Chapel Hill, 1985, ch. 4. On staple theory, see the discussion in Chapter 1,pages 16 and 25, footnotes 21 and 60.

33. On this relationship during the nineteenth century, see North, Economic Growth, pp. 123-25,136-40; C.K. Harley, ‘Western Settlement and the Price of Wheat, 1872-1913’, Journal of Econ-omic History, 38:4, 1978; and idem, ‘Transportation, the World Wheat Trade, and the KuznetsCycle, 1850-1913’, Explorations in Economic History, 17:3, 1980.

34. L. Sawers, ‘The Navigation Acts Revisited’, Economic History Review, 45:2, 1992; J.J.McCusker, ‘British Mercantilist Policies and the American Colonies’, in Engerman and Gallman,eds., Cambridge Economic History, I, pp. 342-43; and B. Baack, ‘British Versus AmericanInterests in Land and the War of American Independence’, Journal of European EconomicHistory, 33:3, 2004. Even in nominally ‘political’ histories of the revolution, these factors loomlarge. For example, F.D. Cogliano, Revolutionary America 1763-1815: A Political History, 2nded., New York, 2000, pp. 61-67;

35. A. Saxton, The Rise and Fall of the White Republic: Class Politics and Mass Culture in Nine-teenth-Century America, London, 1990, p. 145; and D. Walker Howe, What God Hath Wrought:The Transformation of America, 1815-1848, Oxford, 2007, p. 705.

- 106 -

1.4 million square kilometres in 1790 to 4.9 million by 1860.36 The land was

obtained through both purchase and conquest, as the federal government bought land

from France and Russia, annexed large swaths of Mexico, and routinely signed and

broke treaties with the Indians, pushing them into reservations to clear their land for

settlement.37 The new lands incorporated within the expanding frontier were linked to

the old by roads, canals, steamboats, and eventually railways, which drastically

reduced the costs of moving goods over land.38 The terms-of-trade boom was thus

extended to the whole country, allowing settlers to cultivate the new lands. A major

demographic shift followed, with the population rapidly spreading from the land-

scarce east coast toward the West.39 In the Northwest the yeoman settlers would later

be celebrated for their individualistic and independent spirit, which, it was argued,

formed the basis for American democracy,40 but they also formed the militias that

performed the task of exterminating Indians on the frontier. American democracy in

this way came to be based on the collective project of expanding the frontier against

the resistance of the Indians.41

Democratisation turned staple-theory-style extensive (that is, aggregate)

growth into intensive (that is, per capita) growth. As staple theory would predict,

industrialisation occurred due to the numerous linkages that formed between

manufacturing and the export sector.42 Industry would, moreover, become highly

mechanised as a result of the safety-valve effect of the expanding frontier, with the

westward movement ensuring that more easterly labour markets remained tight, so

wages were kept high, which encouraged capitalists to invest in labour-saving tech-

nologies.43 For this reason, the United States’ growth became highly capital-intens-

36. Bureau of the Census, Historical Statistics, p. 428, Series J2.37. B. Vandervort, Indian Wars of Mexico, Canada, and the United States, New York, 2006, chs. 5

and 7; and B. Cumings, Dominion from Sea to Sea: Pacific Ascendancy and American Power,New Haven, 2009, pp. 27-39.

38. North, ‘Role of Transportation’, pp. 221-25; and A. Fishlow, ‘Internal Transportation in the Nine-teenth and Early Twentieth Centuries’, in S.L. Engerman and R.E. Gallman, eds., The CambridgeEconomic History of the United States, II, The Long Nineteenth Century, Cambridge, 2000, pp.548-83.

39. M.R. Haines, ‘The Population of the United States, 1790-1920’, in Engerman and Gallman, eds.,Cambridge Economic History, II, pp. 188-94.

40. Turner, Frontier in American History, ch. 1.41. M. Mann, The Dark Side of Democracy: Explaining Ethnic Cleansing, Cambridge, 2005, pp.

83-98.42. See D.R. Meyer, ‘Emergence of the American Manufacturing Belt: An Interpretation’, Journal of

Historical Geography, 9:2, 1983; and G. Wright, ‘The Origins of American Industrial Success,1879-1940’, American Economic Review, 80:4, 1990.

- 107 -

ive. Already by mid-century there was almost twice as much capital per worker being

sunk into fixed investments as in Britain.44 The North’s victory during the Civil War

of 1861-65 would then see the frontier’s safety-valve effect amplified, as it ensured

that the remaining western lands would become settler, rather than slaveholding,

societies.45 A series of Homestead Acts, beginning during the Civil War, allowed

public lands to be distributed to settlers for free, considerably increasing access to the

land.46 The expanding frontier’s continuing safety-valve effect then encouraged capit-

alists to make further investments in labour-saving technologies, so by the First

World War the capital per worker being put into fixed investments was over three

times the level of Britain.47 Labour productivity was thereby raised, so workers could

enjoy higher wages, which further increased demand for their goods and services.

Such a virtuous circle made the United States increasingly self sufficient, with the

importance of trade decreasing, as illustrated by the falling ratio between interna-

tional trade and GDP in Figure 3.3. This represented the transition from a political

economy based on land-intensive staple production for export to another based on

highly capitalised production oriented toward the domestic market. Ultimately it

would become known as ‘Fordism’ – a situation in which industrial workers were

sufficiently well paid to provide the demand for the goods that they produced.48

43. Habakkuk, American and British Technology, ch. 3.44. Calculated from R.E. Gallman, ‘Gross National Product in the United States, 1834-1909’, in D.S.

Brady, ed., Output, Employment, and Productivity in the United States after 1800, New York,1966, p. 34, Table A-3; Bureau of the Census, Historical Statistics, p. 134, Series 75; C. Fein-stein, National Income, Expenditure and Output of the United Kingdom, 1855-1965, Cambridge,1972, p. T125, Table 57; Mitchell, British Historical Statistics, pp. 831-33; and P.W. Rhode,‘Gallman’s Annual Output Series for the United States, 1834-1909’, NBER Working Paper 8860,2002, pp. 29-32, Tables 2-3. Were the series adjusted for differences in prices, it is likely that USinvestment levels would appear even higher. Cf. Collins and Williamson, ‘Capital-Goods Prices’,pp. 67-68, Table 2. Also see the discussion in Chapter 1, page 25, footnote 61.

45. M.A. Morrison, Slavery and the American West: The Eclipse of Manifest Destiny and the Comingof the Civil War, Chapel Hill, 1997; and J.M. McPherson, This Mighty Scourge: Perspectives onthe Civil War, Oxford, 2007, ch. 1.

46. Economic historians have tended to decrie the inefficiencies of the Homestead Acts. Forexample, J. Atack, F. Bateman, and W.N. Parker, ‘Northern Agriculture and the Westward Move-ment’, in S.L. Engerman and R.E. Gallman, eds., The Cambridge Economic History of the UnitedStates, II, The Long Nineteenth Century, Cambridge, 2000, p. 301. In doing so, however, theyhave generally ignored their undoubtedly massive impact. One estimate suggests that roughly‘one-quarter of the current [that is, early twenty-first-century] US adult population (age 25 andolder) potentially has ancestors who were homesteaders’. T.W. Shanks, ‘The Homestead Act: AMajor Asset-Building Policy in American History, in M. Sherraden, ed., Inclusion in the Amer-ican Dream: Assets, Poverty, and Public Policy, Oxford, 2005, p. 32.

47. Calculated from the same sources as in footnote 44.48. See M. Aglietta, A Theory of Capitalist Regulation: The US Experience, London, (1979) 2000,

pp. 116-22; also M. Davis, ‘‘Fordism’ in Crisis: A Review of Michel Aglietta's ‘Régulation et

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Figure 3.3US Overseas Trade, 1790-1913

0

10

20

30

40

50

1780 1800 1820 1840 1860 1880 1900 1920

% of GDP

Note: Overseas trade includes exports, re-exports, and imports of merchandise.

Sources: Irwin, ‘Exports and Imports’, Series Ee365 and Ee368; and S.H. Williamson, ‘WhatWas the US GDP Then?’, 2013, online at http://www.measuringworth.org/usgdp (accessed 5September 2013).

The FollowersTo different degrees, the other land-abundant countries followed the United States’

development path up to the First World War, although without catching up. Figure

3.4 shows how the density of their railway networks relative to the amount of poten-

tial arable land remained far behind the United States throughout the nineteenth

century, despite the rapid expansion that occurred once massive imports of British

capital allowed them to construct railway networks at breakneck speed from the

1850s and ‘60s onwards.49 Figure 3.5 illustrates how this lateness meant that the

crises: L'expérience des Etats-Unis’, Review (Fernand Braudel Center), 2:2, 1978, pp. 215-17.Fordism was originally known as the ‘high wage doctrine’. It was espoused by Henry Ford andothers at the beginning of the twentieth century. See J.E. Taylor, ‘Did Henry Ford Mean to PayEfficiency Wages?’, Journal of Labor Research, 24:4, 2003.

49. On British investment, see L.E. Davis and R.E. Gallman, Evolving Financial Markets and Inter-national Capital Flows: Britain, the Americas, and Australia, 1865-1914, Cambridge, 2001, pp.377-84, 501, 720-22. Potential arable land has been preferred to total territory in Figure 3.4because the latter can include large quantities of land that could never be productive. Usingpotential arable land therefore gives a better indication of the supply of transportation relative to

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Figure 3.4Railway Density, 1830-1910

0

20

40

60

80

100

120

140

1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920

USA

Can. Arg. Aus.

S. Africa

Braz.

km per km2

Note: The series show the kilometres of railway per square kilometre of land that could beused for rain-fed arable agriculture.

Sources:

Potential arable land: As in Table 3.1.

Railways: ABS, Official Year Book 1907, Canberra, 1908, p. 552; B.R. Mitchell,International Historical Statistics: Africa, Asia and Oceania 1750-2005, 5th ed., Basingstoke,2007, pp. 714, 717, 728; and idem, International Historical Statistics: The Americas,1750-2005, 6th ed., Basingstoke, 2007, pp. 562-65, 567-68.

realisation of their agricultural potential also trailed the United States. The series

gives a rough indication of how much of the six countries’ potential arable land was

being cultivated for crops during the long nineteenth century by showing the amount

of cropland in each as a percentage of the total amount of land that could potentially

have been used for rain-fed arable farming. The result indicates that the United States

was still far ahead by 1910, as almost half of its arable potential was being used,

compared to 30 percent in Canada, from six to eight percent in Argentina, Australia,

and South Africa, and less than one percent in Brazil. It should be stressed that these

figures are approximate, given the shortage of data on historical land usage, particu-

larly for the first half of the nineteenth century.50 Nevertheless, the general picture is

the potential demand for it.

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Figure 3.5Arable Potential Realised, 1780-1910

0

10

20

30

40

50

60

1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920

USA

Canada

Arg.

Aus. S. Africa

Braz.

% used

Note: The series show total cropland in cultivation as a percentage of land that could be usedfor rain-fed arable agriculture.

Sources: As in Table 3.1.

accurate: relatively little of the other land-abundant countries’ agricultural potential

had been realised due to their late start compared to the United States.51

Their lateness prevented the other land-abundant countries from attaining the

same degree of industrialisation as the United States because the linkages predicted

by staple theory were only just forming.52 Consequently, only a relatively low level

50. See Appendix 3.1.51. Much arable land was being used for grazing, particularly in the followers. This, however, was

itself a sign of land under-utilisation, in that, per hectare, arable farming was considerably moreproductive than livestock. In Buenos Aires Province during the first half of the 1880s, forexample, land could typically take four sheep per hectare, each of which produced 1.8 kg ofwool, giving a total yield of 7.2 kg, which sold in the city for o$s2.52, at 35 cents per kg. Bycontrast, a wheat farm could be expected to produce about 700 kg per ha, which would sell in thecity for five cents per kg, giving a total of o$s35. The gross wholesale value of the output wasthus 14 times greater for the wheat farm. Calculated from J. Álvarez, Temas de historia económ-ica argentina, Buenos Aires, 1929, pp. 208-09, 219; Sabato, Agrarian Capitalism, p. 143; andFerreres, Dos siglos, Table 4.1.1. It was, though, far more labour-intensive to produce andexpensive to transport wheat, so most of the potential arable land could not be used for thatpurpose until the arrival of railways and the increase in the labour supply due to immigration. SeeChapter 4 for the case of Argentina.

52. For a particularly useful discussion of this, see C.B. Schedvin, ‘Staples and Regions of Pax Brit-annica’, Economic History Review, 43:4, 1990.

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of industrial capacity had been attained by the First World War. Paul Bairoch estim-

ated, for example, that Canada’s industrial output per capita was 37 percent of the US

level in 1913; in Australia, it was 15 percent; in Brazil, six percent; in South Africa,

five percent;53 and had he included an estimate for Argentina, it would probably have

been around eight percent.54 Estimates for specific sectors confirm this impression.

Hence, Argentina, Australia, and South Africa lacked any significant capacity to

produce cotton textiles, and Brazilian and Canadian output was small.55 Only Canada

produced notable quantities of steel, but its per capita output was just a third of the

US level.56 In all the countries the small domestic market meant that their industry

also suffered from diseconomies of scale that prevented it from becoming competit-

ive with imports, let alone being suitable for exports. Rather, their industrial sectors

tended to be heavily dependent upon protective tariffs.57

Low levels of industrialisation ensured that the other land-abundant countries’

development remained highly outward oriented. Their development strategies were

based on borrowing abroad to build the infrastructure required to bring their abund-

ant quantities of land into production, thereby providing the exports that were needed

to service their debts and pay for sufficient imports to maintain high levels of

consumption and investment.58 Trade, as a result, remained of far greater importance

to the follower countries: whereas US exports and imports together equalled around

10 percent of GDP by the First World War,59 in Australia they were about 42

percent;60 in Canada, 35 percent;61 in South Africa, roughly 40 percent;62 and they

53. Bairoch, ‘International Industrialization Levels’, pp. 302, 330, Tables 12 and 1554. Approximated by adjusting Australia’s industrial output by the ratios between Argentina and

Australia’s dependency rates, share of manufacturing in the labour force, and labour productivityin manufacturing. Calculated from Taylor, ‘External Dependence’, p. 922, Table 4; and E.Frankema and M. Visker, ‘The Reversal of Fortune in Argentina: Exploring Industrial LabourProductivity in Comparison to Australia, 1907-1973’, Tijdschrift voor Sociale en EconomischeGeschiedenis, 8:3, 2011, pp. 76, 86, Tables 1 and 5.

55. According to contemporary estimates, in 1908 the United States had 27.5 million spindles; Brazilhad 1.3 million; Canada, 795,000; Argentina, just 7,500. From Bureau of the Census, ‘Supplyand Distribution of Cotton for the Year Ending August 31, 1908’, Bulletin, 97, 1908, p. 26.

56. League of Nations, Statistical Yearbook 1926, Geneva, 1927, pp. 11, 87, Tables 1 and 50.57. For the case of Canada, the most industrialised of the five, see G. Williams, ‘The National Policy

Tariffs: Industrial Underdevelopment Through Import Substitution’, Canadian Journal of Polit-ical Science, 12:2, 1979; and idem, Not for Export: The International Competitiveness of Cana-dian Manufacturing, 3rd ed., Toronto, 1994, ch. 2.

58. See H.M. Schwartz, In the Dominions of Debt: Historical Perspectives on Dependent Develop-ment, Ithaca, 1989, chs. 2 and 8.

59. See Figure 3.3.60. Annual average for 1909-1913, calculated from M.V. Butlin, ‘A Preliminary Annual Database

1900/01 to 1973/74’, Research Discussion Paper 7701, Reserve Bank of Australia, 1977, Table

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were most likely at similar levels in Argentina and Brazil.63 This outward orientation

could have remarkable results. All five countries experienced dramatic extensive

growth, as was seen in Figure 3.1. Australians and Canadians, moreover, enjoyed

some of the highest living standards and productivity levels in the world. At the other

end of the spectrum, however, Brazil lagged far behind, while Argentina and South

Africa were somewhere in between.64 There was, then, considerable variation among

land-abundant countries, although improved terms of trade brought rapid extensive

growth to all by allowing frontiers to expand. The question of why in some countries,

most paradigmatically the United States, the expanding frontier also had a safety-

valve effect that led to more intensive growth will be returned to in Chapter 4.

The Land-Scarce RegionsThe land-scarce regions were less fortunate because they had few frontiers to expand.

As was seen in Table 3.1, Central America, Eurasia, and most of Africa had relatively

little potential arable land per person at the beginning of the long nineteenth century.

Much of Eurasia’s arable potential had, moreover, already been realised, so frontiers

could not be expanded to incorporate new land to the same degree as in Africa, the

Americas, or Oceania. Notably, both Europe and Asia suffered from such land

scarcity. For such regions, development had to occur by moving labour off the land

into industry. If not, an increasing supply of labour would receive diminishing

returns by being applied to a limited amount of land.65

In Northern Europe the process of moving labour off the land had been ongo-

IV.1.61. Annual average for 1909-1913, calculated from Leacy, Historical Statistics, Series G383 and

G384; and M.C. Urquhart, ‘New Estimates of Gross National Product, Canada 1870-1926: SomeImplications for Canadian Development’, in S.L. Engerman and R.E. Gallman, eds., Long-TermFactors in American Growth, New York, 1986, p. 14, Table 2.1.

62. Annual average for 1911-1913, calculated from CSS, South African Statistics 1994, Pretoria,1994, Tables 16.4 and 21.5.

63. The Montevideo-Oxford Latin American Economic History Database (MOxLAD) suggests anaverage trade ratio of 30 percent for Brazil and 38 percent for Argentina during 1909-1913(online at http://moxlad.fcs.edu.uy/en/databaseaccess.html, accessed 7 September 2013). Yet it isimpossible to see how the authors of this database arrived at nominal GDP series for these twocountries, as the reference they provide (B.R. Mitchell, International Historical Statistics: TheAmericas, 1750-1988, Basingstoke, 1993) does not give such series.

64. Living standards in all these countries except South Africa will be assessed in Chapter 5. InSouth Africa, predictably, there was a major difference between the welfare of Europeans andnatives. P. de Zwart, ‘South African Living Standards in Global Perspective, 1835–1910’, Econ-omic History of Developing Regions, 26:1, 2011.

65. Lewis, ‘Economic Development’, pp. 140-43.

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ing since the end of the Middle Ages.66 Most notably, Britain’s agricultural popula-

tion had fallen from around three quarters of its total population at the beginning of

the sixteenth century to just a third by the early nineteenth century.67 Trade made this

shift possible by augmenting the demand for British labour through the extension of

the market for its goods and services.68 Wages were in this way kept high, so capital-

ists sought to invest in labour-saving machinery, which inspired a wave of inventive

activity that led to the British industrial revolution.69 As industrial productivity

increased and the labour force continued to shift from agriculture, trade had to take a

rising share of Britain’s growing surplus of manufactures, given the limited size of its

own market. Hence, by the end of the nineteenth century 80 percent of Britain’s

annual production of cotton goods was being exported, as was 40 percent of its iron

and steel manufactures.70

The counterpart of the core’s progress became the periphery’s decline, as the

cheap manufactures being produced by the industrial revolution undermined the

cottage industries that had previously provided employment outside of agriculture.

This process was essential to the North Atlantic core’s industrial revolution because

exports to the periphery allowed the ‘production possibility frontier’ to expand.71

Around half of British exports consistently went to regions beyond the North Atlantic

during the eighteenth and nineteenth centuries,72 and without the expanded market

that came from these exports, mechanised factory production would have produced

gluts on the domestic market, driving down profitability. The periphery’s markets

were, for this reason, required for the core’s industrialisation. In southern Europe,

66. R.C. Allen, ‘Economic Structure and Agricultural Productivity in Europe, 1300-1800’, EuropeanReview of Economic History, 4:1, 2000; and idem, British Industrial Revolution, pp. 16-22.

67. Allen, ‘Economic Structure’, p. 9, Table 2; and P. Deane and W.A. Cole, British EconomicGrowth 1688-1959, 2nd ed., Cambridge, 1969, p. 141, Table 30.

68. O’Brien and S.L. Engerman, ‘Exports and the Growth’, p. 189.69. Allen, British Industrial Revolution. For a useful discussion of Allen’s analysis, see N. Crafts,

‘Explaining the First Industrial Revolution: Two Views’, European Review of Economic History,15:1, 2011.

70. Deane and Cole, British Economic Growth, pp. 187, 225, Tables 43 and 56. Also see CuencaEsteban, ‘Rising Share’.

71. See P.K. O’Brien, ‘Imperialism and the Rise and Decline of the British Economy, 1688–1989’,New Left Review, 238, 1999, pp. 60-62. This observation is particularly important because itrefutes the same author’s previous (but still widely cited) conclusion that ‘for the economicgrowth of the core, the periphery was peripheral’ (in idem, ‘European Economic Development:The Contribution of the Periphery’, Economic History Review, 35:1, 1982, p. 18).

72. R. Davis, The Industrial Revolution and British Overseas Trade, Leicester, 1979, p. 89, Table 38;and Mitchell, British Historical Statistics, pp. 496-502.

- 114 -

particularly Italy, deindustrialisation had already taken place in the seventeenth and

eighteenth centuries due to competition with England’s fine woollen cloths, the ‘new

draperies’.73 In the nineteenth century a similar deindustrialisation would then occur

across the land-scarce periphery, as cottage industries virtually everywhere were

undermined by cheap British imports.74 Hence, even as the populations of the land-

scarce core were able to move into industry, those of the similarly land-scarce peri-

phery became increasingly concentrated in agriculture.

Pace Lévy-Leboyer, the periphery’s deindustrialisation tended to depress

living standards because specialisation in agriculture meant that a greater supply of

labour had to work a more or less fixed quantity of land, resulting in diminishing

returns that depressed average labour productivity. Here, then, is Frank’s ‘develop-

ment of underdevelopment’, in that the development of one part of the world caused

and required the underdevelopment of another.75 Improving terms of trade drove this

process by depressing the prices of (import-competing) manufactures relative to the

prices of (exportable) raw materials. The consequence was to squeeze profit margins

in the periphery’s cottage industries, so people instead turned to a limited supply of

land for employment. Contrary to the assumptions inherited from the Prebisch-Singer

Hypothesis, therefore, where land was scarce, improved terms of trade actually

tended to cause underdevelopment.76

The nineteenth-century divergence between Northern Europe and the poor

periphery can be illustrated using Allen’s welfare ratios. Figure 3.6 reproduces the

estimates of Allen and his associates for the welfare ratios of unskilled labourers in

two places in Northern Europe and three in the Eurasian periphery. As Table 3.2

indicated, there was already a gap between London and the rest of Eurasia at the end

of the eighteenth century. Figure 3.7 confirms this, as from the 1720s through the

1760s welfare ratios in Beijing, Bengal, Leipzig, and Milan were all 30 to 40 percent

73. R.T. Rapp, ‘The Unmaking of the Mediterranean Trade Hegemony: International Trade Rivalryand the Commercial Revolution’, Journal of Economic History, 35:3, 1975; and C.M. Cipolla,Before the Industrial Revolution: European Society and Economy, 1000-1700, London, 1976, pp.236-44.

74. Apart from the case of India, discussed in Chapter 2, pages 80-84, and further below, see Issawi,An Economic History; Pamuk, Ottoman Empire, ch. 6; Salvucci, Textiles and Capitalism, ch. 5;Amsden, Rise of ‘the Rest’, pp. 33-39; and van der Eng, ‘Why Didn’t Colonial Indonesia’.

75. Frank, Latin America, ch. 1.76. It should be stressed again that the Prebisch-Singer Hypothesis was an intrinsic part of ‘structur-

alism’ but not of ‘dependency theory’. See page 96, footnote 3.

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Figure 3.6Welfare Ratios of Unskilled Labourers in Eurasia, 1730-1913

0

1

2

3

4

5

6

7

8

9

1720 1740 1760 1780 1800 1820 1840 1860 1880 1900 1920

Welfare ratio* London

Milan

Beijing

Leipzig

Bengal

Note: The wage of an unskilled labourer divided by the cost of a basket of goods sufficientfor a subsistence-level standard of living for a man, a woman, and two children.

Sources: R.C. Allen et al, ‘Wages, Prices, and Living Standards in China, 1738-1925: inComparison with Europe, Japan, and India’, Economic History Review, 64:S1, 2011; dataavailable online at http://gpih.ucdavis.edu/files/China_1730-1933_Allen_et_al.xls (accessed 2January 2012).

of the level in London.77 But from then on the welfare ratios in both London and

Leipzig increased rapidly, whereas they fell in the peripheral locations, only recover-

ing somewhat in the second half of the nineteenth century. By the eve of the First

World War, their welfare ratios were all around 20 percent of the level in London,

while they had also fallen to a third of the level in Leipzig.78 This was the bifurcation

between the land-scarce regions of the poor periphery and the North Atlantic core

77. Welfare ratios in the rest of Britain were probably also below London levels. See Malanima,‘When Did England’, pp. 54-58.

78. Much as Australia and Canada had followed the United States, Germany and the late industrial-isers of continental Europe were following Britain. Exports to the periphery did not play a majorrole in their development, although exports to Britain did. Taking continental western Europe as awhole, 50 percent of exports outside of the bloc went to Britain in 1900, as did 38 percent in1913. Calculated from United Nations, ‘International Trade Statistics 1900-1960’, mimeo, 1962,Table 24. Britain’s imports were in turn substantially paid for using receipts from its exports tothe periphery, as well as profits and interest on foreign investments that were largely concentratedin the land-abundant countries. See S.B. Saul, Studies in British Overseas Trade, 1870-1914,Liverpool, 1960, chs. 3-4.

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during the long nineteenth century.

British imperialism helped engineer this divergence by promoting trade

liberalisation in the periphery. Before the nineteenth century monopolies dominated

overseas trade within European empires. They had been conceived of and had

become important components of state finance, with companies granted licenses to

trade with the colonies on the condition that all exports and imports passed through

the mother country, where they could be taxed.79 This kept trade costs high because

there was a lack of competition among merchants, and numerous taxes were imposed

on traded goods, both in Europe and the colonies. Inadvertently, high trade costs then

gave some protection to the colonies’ cottage industries by reducing the competitive-

ness of European manufactures in the colonies’ market. In the first half of the nine-

teenth century, however, those monopolies were steadily abolished,80 in large part

thanks to the growth of British influence.

The British government sought access to foreign markets for its country’s

manufactures because it was aware that British industry faced the threat of glut on

the home market, which could lead to recessions that would have increased domestic

unrest.81 The extension of British power therefore tended to be followed by trade

liberalisation. Hence, in exchange for aiding his escape from Napoleon in 1807, the

British government obliged the Prince Regent of Portugal to open Brazil’s trade,

rapidly bringing his country’s trading monopoly to an end;82 similarly, the promise of

trade with Britain helped inspire the revolutionaries who fought the Spanish empire

79. Hamilton, ‘Role of Monopoly’; P. Bairoch, ‘European Trade Policy, 1815-1914’, in P. Mathiasand S. Pollard, eds., The Cambridge Economic History of Europe, VIII, The Industrial Econom-ies: The Development of Economic and Social Policies, Cambridge, 1989, p. 103; McCusker,‘British Mercantilist Policies’, pp. 342-43; and R. Torres Sánchez, ‘The Triumph of the FiscalMilitary State in the Eighteenth Century: War and Mercantilism’, in idem, ed., War, State andDevelopment: Fiscal-Military States in the Eighteenth Century, Pamplona, 2007, pp. 32-33,39-40.

80. Bairoch, ‘European Trade Policy’, pp. 107-27, 150-60.81. P.J. Cain and A.G. Hopkins, ‘The Political Economy of British Expansion Overseas, 1750-1914’,

Economic History Review, 33:4, 1980, pp. 475-81; and idem, British Imperialism, pp. 84-85,99-100, 102. This is a mildly revised version of the argument made in J. Gallagher and R. Robin-son, ‘The Imperialism of Free Trade’, Economic History Review, 6:1, 1953; also see B. Semmel,The Rise of Free Trade Imperialism: Classical Political Economy, the Empire of Free Trade, andImperialism, 1750-1850, Cambridge, 1970, pp. 9-10, ch. 6. For the debate surrounding Gallagherand Robinson’s arguments, see Webster, Debate on the Rise, ch. 4.

82. L. Bethell, ‘The Independence of Brazil’, in idem, ed., The Cambridge History of Latin America,III, From Independence to c. 1870, Cambridge, 1985, pp. 168-73; and J.M. Pedreira, ‘FromGrowth to Collapse: Portugal, Brazil, and the Breakdown of the Old Colonial System(1750-1830)’, Hispanic American Historical Review, 80:4, 2000, pp. 849-53.

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in the 1810s and ‘20s;83 the persistent lobbying of British merchants and manufactur-

ers led to the abolition of the East India’s Company’s trading monopolies with India

and China in 1813 and 1833 respectively;84 the Ottoman Empire was opened by the

Anglo-Turkish Convention in 1838;85 British gunboats forced China to open through

the Opium War of 1839-42,86 which inspired US gunboats to do the same in Japan

during 1853-54.87 Such widespread liberalisation left cottage industries across the

periphery exposed to the influx of cheap manufactured goods being produced by the

industrial revolution.

India was the archetypal case of how British imperialism brought deindustri-

alisation to the periphery.88 In the eighteenth century, Robert Clive had reported that

India was the ‘Paradise of the Earth’ because it abounded ‘in very curious and valu-

able manufactures, sufficient not only for its own use, but for the use of the whole

Globe. The Silver of the West and the Gold of the East’, Clive continued, ‘have for

many years been pouring into that Country, and Goods only have been sent out in

return’.89 There were, in other words, few European goods that Indians required, so

Europe had been forced to pay for Indian manufactures, especially its textiles, with

bullion.90 The solution to this outflow of precious metals, pioneered by Clive’s East

India Company, had been to establish a company state that used tax revenues to

83. J. Lynch, The Spanish American Revolutions, 1808-1826, 2nd ed., London, 1986, pp. 13-16; M.P.Costeloe, ‘Spain and the Latin American Wars of Independence: The Free Trade Controversy,1810-1820’, Hispanic American Historical Review, 61:2, 1981, pp. 209-34; and J. Adelman,Sovereignty and Revolution in the Iberian Atlantic, Princeton, 2006, pp. 172, 202-06.

84. A. Webster, ‘The Strategies and Limits of Gentlemanly Capitalism: The London East IndiaAgency Houses, Provincial Commercial Interests, and the Evolution of British Economic Policyin South and South East Asia 1800–50’, Economic History Review, 59:4, 2006, pp. 743-64; idem,The Twilight of the East India Company: The Evolution of Anglo-Asian Commerce and Politics,1790-1860, Woodbridge, 2009, chs. 3 and 5; and Y. Kumagai, Breaking into the Monopoly:Provincial Merchants and Manufacturers’ Campaigns for Access to the Asian Market,1790-1833, Leiden, 2013.

85. Issawi, Economic History, p. 19; Pamuk, Ottoman Empire, p. 20; and Cain and Hopkins, BritishImperialism, p. 342.

86. J.K. Fairbank, ‘The Creation of the Treaty System’, in idem, ed., The Cambridge History ofChina, X, Late Ch’ing, 1800-1911, Part I, Cambridge, 1978, pp. 221-22; and Cain and Hopkins,British Imperialism, pp. 362-63.

87. W.G. Beasly, ‘The Foreign Threat and the Opening of the Ports’, in M.B. Jansen, ed., TheCambridge History of Japan, V, The Nineteenth Century, Cambridge, 1989, pp. 268-70.

88. For the debate, see Habib, ‘Studying a Colonial Economy’, pp. 359-64; Roy, Rethinking Econ-omic Change, ch. 5; and Parthasarathi, ‘Historical Issues’.

89. R. Clive, Lord Clive’s Speech, London, 1772, p. 42.90. See K.N. Chaudhuri, ‘Treasure and Trade Balances: The East India Company’s Export Trade,

1660-1720’, Economic History Review, 21:3, 1968, pp. 480-502; and O. Prakash, ‘Bullion forGoods: International Trade and the Economy of Early Eighteenth Century Bengal’, Indian Econ-omic and Social History Review, 13:2, 1976, pp. 159-86.

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purchase Indian textiles, which weavers were forced to provide at lower prices.91 The

industrial revolution undermined this trade, however, because falling prices made

British textiles competitive on the Indian market. Technical innovations on North

American cotton plantations, together with improved packing and shipping, had

reduced the price of raw cotton in Britain, while a series of mechanical inventions –

the spinning jenny, water frame, and spinning mule – had substantially increased

labour productivity in British textile manufacturing in the 1760s and ‘70s, compensa-

ting for wages that were considerably higher than in India.92 Aware of their greater

competitiveness and in need of an outlet for their expanding surplus, British

manufacturers lobbied for their products to be given access to the Indian market,

which helped persuade the British government to recast India as a supplier of

primary commodities. The abolition of the East India Company’s trade monopoly

followed in 1813,93 with the Company thereafter obliged to permit British textiles

into India at minimal tariff rates. From virtually nothing at the end of the eighteenth

century, the British share of the Indian cotton textile market then increased to a peak

of around 60 percent by 1880, as India’s own production of cotton cloth fell by

perhaps a third, and exports of raw cotton grew by over 400 percent.94 Rising costs of

raw materials, combined with the falling prices of imported textiles, then squeezed

the incomes of spinners and weavers. Consequently, employment in India’s textiles

sector fell, both as a percentage of the labour force and absolutely.95

91. P. Parthasarathi, The Transition to a Colonial Economy: Weavers, Merchants and Kings in SouthIndia, 1720-1800, Cambridge, 2001, ch. 3; O. Prakash, ‘From Market-Determined to Coercion-Based: Textile Manufacturing in Eighteenth-Century Bengal’, in Riello and Roy, eds., How IndiaClothed the World, pp. 217-52; and H. Hossain, The Company Weavers of Bengal: The East IndiaCompany and the Organization of Textile Production in Bengal 1750-1913, Dhaka, 2010, ch. 4.

92. S. Broadberry and B. Gupta, ‘Lancashire, India, and Shifting Competitive Advantage in CottonTextiles, 1700-1850: The Neglected Role of Factor Prices’, Economic History Review, 62:2,2009, pp. 290-93, Table 8. Wage data for India, particularly for weavers, is problematic, soBroadberry and Gupta’s findings should be treated with caution. See Parthasarathi, ‘HistoricalIssues’, pp. 419-22; and idem, Why Europe Grew, pp. 42-44. On the falling transportation costsfor US cotton, see Harley, ‘Ocean Freight Rates’, pp. 856-60.

93. A. Webster, ‘The Political Economy of Trade Liberalization: The East India Company CharterAct of 1813’, Economic History Review, 43:3, 1990, pp. 404-19; idem, Twilight of the East IndiaCompany, chs. 3 and 5; and Kumagai, Breaking into the Monopoly, chs. 2 and 4.

94. Roy, ‘Consumption of Cotton Cloth’, pp. 72-73, Tables 2 and 3.95. A. Bagchi, ‘Deindustrialization in Gangetic Bihar 1809-1901’, in B. De et al, eds., Essays in

Honour of Prof. S.C. Sarkar, New Delhi, 1976, pp. 499-523; M.J. Twomey, ‘Employment inNineteenth Century Indian Textiles’, Explorations in Economic History, 20:1, 1983, pp. 37-57;and Clingingsmith and Williamson, ‘Deindustrialization in 18th and 19th Century in India’, pp.218-20. Even a highly skeptical historian suggests that ‘[i]t is possible, indeed likely, that if wehad a good occupational census for 1750 or 1800, the percentage of industrial workers in the totalworkforce would be as high as 25-30, which collapsed to 8-9 at 1900’. Roy, Rethinking Econ-

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The decline of cottage industries resulted in a widespread ‘traditionalisation’

of Indian society that saw it become increasingly agrarian.96 Many of the subcontin-

ent’s largest cities shrank,97 and the countryside’s population of peasants and landless

labourers grew. Social conflict then mounted due to a growing population’s attempts

to work a limited amount of land: landowners clashed with the Company over taxes,

landlords with tenants over rents, and peasants with tribal peoples over access to

land. Eventually this growing discontent culminated in the mutiny of the Company’s

army in 1857.98 Subsequently, the Company itself was abolished and India was form-

ally annexed by the British government, with direct rule used to continue India’s

conversion into an exporter of agricultural staples. Major infrastructure projects,

particularly railways, were promoted to connect the interior to the ports,99 which

allowed exports of cotton, opium, tea, jute, rice, and even wheat to expand

massively.100 What data there are, however, suggest that this export expansion came

at the expense of food production for domestic consumption.101 India’s conversion

into an exporter of primary commodities in this way undermined food security, as

was seen most clearly when tens of millions of people perished during the great

famines of the 1870s and ‘90s.102

India’s fate during the nineteenth century was broadly representative of the

land-scarce periphery as a whole. Across much of Africa, Asia, and Central America

deindustrialisation pushed more workers onto a limited quantity of land, leading to

rapidly diminishing returns that depressed average productivity levels. Moreover, to

the extent that the periphery’s industry competed with that of the North Atlantic core,

omic Change, p. 102.96. C.A. Bayly, The New Cambridge History of India, I:1, Indian Society and the Making of the Brit-

ish Empire, Cambridge, 1988, chs. 4-5; and D. Washbrook, ‘South India 1770-1840: The Colo-nial Transition’, Modern Asian Studies, 38:3, 2004, pp. 479-516.

97. Habib, ‘Studying a Colonial Economy’, pp. 364-68.98. Bayly, New Cambridge History of India, pp. 170-71.99. D.R. Headrick, The Tentacles of Progress: Technology Transfer in the Age of Imperialism,

1850-1940, New York, 1990, pp. 58-78.100. K.N. Chaudhuri, ‘Foreign Trade and Balance of Payments (1757-1947)’, in D. Kumar and M.

Desai, eds., The Cambridge Economic History of India, II, c. 1757-c. 1970, Cambridge, 1983, pp.841-60.

101. G. Sumit, ‘Introduction’, in idem, ed. Growth, Stagnation, or Decline? Agricultural Productivityin British India, Delhi, 1992, pp. 1-48.

102. D. Washbrook, ‘The Commercialization of Agriculture in Colonial India: Production, Subsistenceand Reproduction in the 'Dry South', c. 1870-1930’, Modern Asian Studies, 28:1, 1994, pp.129-64; and M. Davis, Late Victorian Holocausts: El Niño Famines and the Making of the ThirdWorld, London, 2001, chs. 1, 5, and 10.

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it was by employing more labour, rather than by investing in technology. The ‘over-

population’ that resulted from deindustrialisation – that is, from a falling share of

industrial employment in the labour force – thus ensured that what industry the peri-

phery had also suffered from low levels of labour productivity.103 Only in the second

half of the nineteenth century would the population pressure be somewhat relieved

due to mass emigration.104 Most famously, around 40 million Europeans moved to

North and South America, possibly leading to some convergence in transatlantic

living standards.105 Even more Chinese and Indians emigrated as well, but where they

went was limited by a variety of restrictions placed on their entry by the governments

of the land-abundant countries in North America and Oceania.106 Accordingly, they

mainly went to the less densely populated areas of the Pacific, Manchuria, Central

Asia, and Siberia. The restrictions on their migration thus reinforced the inequities of

the new global order.

The Global ReorderingGlobal divergence in the long nineteenth century occurred, then, through what Frank

called the ‘underdevelopment of development’, as the same fundamental cause, the

long terms-of-trade boom, brought prosperity to some regions but stagnation to

others, largely depending upon their endowments of land and labour. The long boom

103. The results of this labour-intensive (re)industrialisation are analysed by G. Clark, ‘Why Isn't theWhole World Developed? Lessons from the Cotton Mills’, Journal of Economic History, 47:1,1987, pp. 141-73; also see idem, A Farewell to Alms: A Brief Economic History of the World,Princeton, 2007, ch. 16. Clark’s own interpretation of his findings is wrong because he assumesthat the marginal productivity of labour in the periphery’s industry was zero, so there was nogood reason for industrialists to keep on employing more labour. This, however, was not the case.See R.C. Allen, ‘A Review of Gregory Clark's A Farewell to Alms: A Brief Economic History ofthe World’, Journal of Economic Literature, 46:4, 2008, pp. 967-68. For this reason, it madesense for industrialists to keep on employing more workers at subsistence-level wages, ratherthan invest in machinery and equipment. Again, on the close connection between such invest-ments and average productivity levels, see Allen, ‘Technology and the Great Divergence’.

104. For an overview, see A. McKeown, ‘Global Migration, 1846-1940’, Journal of World History,15:2, 2004, pp. 155-89.

105. J.G. Williamson, ‘The Evolution of Global Labor Markets since 1830: Background Evidence andHypotheses’, Explorations in Economic History, 32:2, 1995, pp. 153-57. On some doubts overthis conclusion, see S. Larsson, ‘Globalisation, Inequality and Swedish Catch Up in the LateNineteenth Century’, Göteborg Paper in Economic History 2, Göteborg University, 2005; and S.Prado, ‘Fallacious Convergence? Williamson’s Real Wage Comparisons under Scrutiny’, Clio-metrica, 2010, 4:2, 2011, pp. 171-205.

106. C.A. Price, The Great White Walls Are Built: Restrictive Immigration to North America andAustralasia 1836-1888, Canberra, 1974; and R.A. Huttenback, Racism and Empire: WhiteSettlers and Colored Immigrants in the British Self-Governing Colonies, 1830-1910, Ithaca,1976.

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triggered what has variously been called the ‘great land rush’ or the ‘settler revolu-

tion’, beginning in the British American colonies in the eighteenth century, then

spreading across the world’s land-abundant regions in the nineteenth century.107

Settlers rushed to dispossess indigenous peoples because improved terms of trade

allowed their land to be profitably brought into production for the first time.

Consequently, during the long nineteenth century a country’s arable potential became

the principal determinant of the degree to which its population grew. For the prosper-

ous European offshoots, extensive growth would then become intensive growth as

the safety-valve effect of the expanding frontier kept wages high, so capitalists were

encouraged to invest in labour-saving technologies, which raised average productiv-

ity levels. Where land was scarce, by contrast, development had to occur by moving

labour out of agriculture into other, higher productivity activities – a process that

occurred in the North Atlantic core at the expense of cottage industries in the land-

scarce periphery. As deindustrialisation set in, much of the periphery became ‘over-

populated’, as increased quantities of labour were applied to limited amounts of land,

bringing rapidly diminishing returns that lowered average productivity levels.108 The

land-scarce periphery thus stagnated due to deindustrialisation, even as the similarly

land-scarce North Atlantic core prospered by moving labour out of agriculture into

manufacturing. In this way, the world was reordered.

To understand why this reordering occurred, this chapter has looked at the

global political economy of the long boom. It has argued that the terms of trade did

not improve simply because of ‘exogenous shocks’; specifically, the long boom was

not just due to technological change, whether improved shipping or the mechanisa-

tion of manufacturing. Rather, government policies, especially those associated with

the impacts of British imperialism, played a major role. As Adam Smith realised, the

relatively benevolent terms of trade enjoyed by the British American colonies in the

107. Weaver, Great Land Rush; and J. Belich, Replenishing the Earth: The Settler Revolution and theRise of the Angloworld, Oxford, 2009. Both these studies ascribe the phenomenon that theydescribe to the nineteenth-century zeitgeist of European expansionism – for Belich, in particular,it appears as a result of a kind of collective hysteria whipped up by propagandists for overseascolonisation (see ibid., esp. 153-65). By contrast, the explanation given here, which will befurther developed in Chapter 4, is that these periods of exuberance responded to increased oppor-tunities for profit due to improved terms of trade.

108. ‘Overpopulated’ must be placed in inverted commas because in fact the North Atlantic core wasmore overcrowded, in terms of population density, than much of the poor periphery. The differ-ence was that there was less underemployment in the core because there was more industry.

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eighteenth century were thanks to a liberal trade policy that encouraged more

competition among merchants, which squeezed their profit margins, thereby putting

pressure upon them to reduce trade costs. Similarly, British pressure to liberalise the

periphery’s overseas trade in the first half of the nineteenth century played an import-

ant role in starting the long boom elsewhere, as the various European trade monopol-

ies were undermined. Improving terms of trade then generated the new global order

in which the North Atlantic core industrialised, the European offshoots prospered,

and the poor periphery stagnated.

As has been mentioned in this chapter, Argentina was a land-abundant coun-

try, comparable to the European offshoots in terms of its arable potential and nine-

teenth-century population growth. Yet, as Chapter 4 will discuss, it was unlike them

because it had been colonised by Europeans considerably earlier, so it was not a

‘country of recent settlement’. Crucially, this earlier settlement meant that, unlike

those countries, it had a more densely populated interior that lost out once the long

boom began. The consequence would be several decades of civil war following inde-

pendence in 1810, eventually leading to the formation of an oligarchic state that

substantially represented the interests of the ruling classes of the country’s land-

scarce regions. There would, as a result, be no white-egalitarian democracy in Argen-

tina, which, Chapter 4 will argue, would prevent it from realising its potential as a

land-abundant country.

Appendix 3.1: Land and Population in 166 CountriesThis chapter has drawn on two datasets of land and population in 166 countries. Both

datasets include the same estimate of the amount of land that could potentially be

used for rain-fed agriculture in each country (that is, each country’s arable potential),

as calculated by the United Nation’s Food and Agriculture Organisation (FAO).109

The first dataset, which is reproduced in Table DA.9 in the Data Appendix, combines

this FAO data with estimates of global cropland coverage during 1780-1910 from the

Netherlands Environmental Assessment Agency’s History Database of the Global

Environment (HYDE).110 The second database, reproduced in Table DA.10, provides

a longer-term perspective by combining the potential arable land series with the

109. Bort, Nachtergaele, and Young, ‘Land Resource Potential’, pp. 37-38.110. van Drecht and de Vos, ‘HYDE 3.1’.

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HYDE estimates of each country’s population from 1500 to 1900

It must be stressed that these figures suffer from considerable margins of

error, so the figures contained in Tables DA.9 and DA.10 must be treated as indicat-

ive rather than precise. Estimating historical populations, for instance, is not an easy

task.111 In fact, it is impossible to know past populations of most places with a high

degree of accuracy, as seen most clearly in the long debate about the number of indi-

genous Americans prior to colonisation.112 In this respect, the HYDE database

appears an improvement on some previous compilations,113 although it is still not

without its problems. Figure A3.1 illustrates this by comparing its series for Argen-

tina’s population during 1500-1900 with that of Alfredo Lattes,114 one of the coun-

try’s leading historical demographers. Whereas the HYDE series is constant from

1500 to 1800, Lattes estimates that the population fell after the arrival of the Spanish,

then recovered somewhat prior to the nineteenth century’s rapid expansion – a

pattern that seems more likely. The HYDE estimates are, then, far from perfect.

Similarly, the HYDE data on historical croplands are speculative, although comparis-

ons with Argentina’s official statistics on cultivated land in the twentieth century

suggest that they are preferable to the Global Land Use Database of the Center for

Sustainability and the Global Environment (SAGE).115 For instance, the SAGE data-

base inexplicably claims that Argentina had 45 million hectares of cropland in 1940,

even though Argentine government statistics, as well as HYDE, put the figure at 22

million.116 Such anomalies in the SAGE database mean that HYDE has been

preferred here.

111. Platt, Mickey Mouse Numbers, pp. 20-23, 34-35; and Austin, ‘Reversal of Fortune’, pp. 1001-03.112. For a summary, see L. Bethell, ‘A Note on the Native American Population on the Eve of the

European Invasions’, idem, ed., The Cambridge History of Latin America, I, Colonial LatinAmerica, Cambridge, 1984, pp. 145-46.

113. Especially C. McEvedy and R. Jones, Atlas of World Population History, Harmondsworth, 1978;and Maddison, World Economy, II.

114. A.E. Lattes, ‘Perspectiva histórica de la evolución de la población’, in Recchini de Lattes andLattes, eds., Población de Argentina, p. 23, Cuadro 1.1.

115. SAGE, ‘Global Land Use Database’, available online at http://www.sage.wisc.edu/iamdata/(accessed 5 September 2013).

116. For the official series, see INDEC, Anuario Estadístico 1981-82, Buenos Aires, 1984, pp. 447-49.

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Figure A3.1Argentina’s Population, 1500-1900

100

1000

10000

1500 1550 1600 1650 1700 1750 1800 1850 1900

HYDE

Lattes

1,000 people, log scale

Sources: Lattes, ‘Perspectiva histórica’, p. 23, Cuadro 1.1; and van Drecht and de Vos,‘HYDE 3.1’.

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Chapter 4

Reordering the River Plate

If any worthy alderman had supped with us that evening, ‘carne con cuero’, withoutdoubt, would soon have been celebrated in London.

Charles Darwin, The Voyage of the Beagle1

Argentina too was shaped by its own long boom, as the new nation emerged during

the global reordering. This chapter demonstrates that Argentina’s terms-of-trade

boom was far greater than has previously been supposed, and its effects more

profound, as it allowed the land-abundant Littoral to prosper while it also made the

relatively land-scarce (or, initially, landlocked) interior stagnate. As Miron Burgin

recognised in a classic study, it was these uneven impacts of the long boom that

prevented the formation of a unified state in Argentina for several decades after inde-

pendence in 1810.2 Here Burgin’s account is extended up to the First World War

through an analysis of the role played by the terms of trade in the process of state

formation from the 1860s onwards. The chapter argues that the presence of the stagn-

ant interior prevented democratisation, so access to the land was restricted, which

muted the safety-valve effect of the expanding frontier. Consequently, the kind of

intensive growth experienced in the European offshoots was limited in Argentina, so

it did not fulfil its potential as a land-abundant country.

This chapter in this way provides a pessimistic revision of Argentina’s long

nineteenth century. It begins by discussing the extent and origins of the terms-of-

trade boom. By taking into account the methodological findings of Chapter 2, it

shows that the improvement in Argentina’s terms of trade has been massively under-

estimated. Most likely, they improved by at least 2,000 percent from the 1780s to the

first decade of the twentieth century. Initially this was due to trade liberalisation

1. C. Darwin, The Voyage of the Beagle, New York, (1835) 1909, p. 2052. Burgin, Economic Aspects, esp. ch. 1. Also see the discussion in Chapter 1, pages 31-32.

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under the impact of British imperialism, then it continued because of the falling

prices of the core’s manufactured goods, combined with lower trade costs. Having

demonstrated its extent, the chapter then discusses how this long boom disordered

the River Plate by generating decades of intermittent civil conflict that prevented the

formation of a unified state. Only with the onset of massive British investment from

the 1860s onwards would a unified state be able to form, as a British-financed rail-

way network increased the federal government’s capacity to protect its supporters in

the provinces.3 The new state was oligarchic, it is argued, because the losers from the

long boom – the interior’s peasantries – had to be excluded from politics. A lack of

democratisation then prevented the kind of white-egalitarian policies that facilitated

access to the land in the European offshoots, so the expanding frontier’s safety-valve

effect was muted. Argentina, as a result, began the twentieth century in the paradox-

ical position of being a land-abundant country with widespread landlessness, which

prevented it from fulfilling its potential. Chapter 5 will go on to confirm this pessim-

istic revision by showing that living standards in Argentina remained considerably

below the levels of the world’s most developed countries prior to the First World

War.

The Imperial ImpactArgentina itself played a small but important role in bringing the new global order

into being. During the French Wars Britain had sought the dissolution of the Spanish

empire because American silver was flowing to France via Spain, while new export

markets were also needed as a result of Napoleon’s prohibition of British goods from

continental Europe in 1806. Yet British politicians were unsure what to promote in

the Spanish empire’s place, as they vacillated between seeking to colonise Spanish

America themselves and supporting the formation of independent states.4 A synthesis

would only emerge following the two failed invasions of Buenos Aires in 1806 and

1807. In the first invasion, the commander of a British naval squadron took it upon

3. As discussed in Chapter 1, pages 33-34, this interpretation of Argentina’s state formation issubstantially inspired by de la Fuente, Children of Facundo; also see G.L. Paz, ‘Province andNation in Northern Argentina: Peasants, Elite and the State, Jujuy, 1790-1880’, PhD diss., EmoryUniversity, 1999.

4. J. Lynch, ‘British Policy and Spanish America, 1783-1808’, Journal of Latin American Studies,1:1, 1969, pp. 1-4, 23; and K. Gallo, Great Britain and Argentina: From Invasion to Recognition,1806-26, New York, 2001, ch. 1.

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himself to occupy the city, in order to permit the merchants who accompanied him to

disembark their goods. After four months, however, his forces were expelled by the

Spanish army and militias formed by the city’s inhabitants and gauchos (the rural

poor).5 This failure of the British invasions inspired a major shift in British policy

towards a synthesis of colonisation and supporting independence.6

Viscount Castlereagh, then Secretary of State for War, outlined the British

policy toward South America in a cabinet memorandum soon after the failure of the

first invasion of Buenos Aires. He maintained that it would be unwise to engage

further in ‘the hopeless task of conquering this extensive country, against the temper

of its population’,7 but at the same time, neither should Britain unconditionally

promote independence from Spain due to the ‘probability that any local government

which might be established would become democratic and revolutionary, and that, in

endeavouring to promote and combine the happiness of the people with extension of

our own commerce, we might, in destroying a bad government, leave them without

any government at all’.8 Instead, Castlereagh argued, the British government should

support the formation of a sovereign state that would be governed by a local ruling

class that was amenable to British interests. Given that it has previously been misin-

terpreted, Castlereagh’s conclusion is worth quoting at length.9 He wrote:

In looking to any scheme for liberating South America, it seems indispensable thatwe should not present ourselves in any other light than as auxiliaries and protectors.In order to prove our sincerity in this respect, we should be prepared to pursue ourobject by a native force, to be created under our countenance; and the particularinterest which we should be understood alone to propose to ourselves should be thedepriving our enemy of one of his chief resources, and the opening to our manufac-tures the markets of that great Continent.10

5. H.S. Ferns, Britain and Argentina in the Nineteenth Century, Oxford, 1960, pp. 20-35; and Gallo,Great Britain and Argentina, pp. 37-41.

6. Cf. Ferns, Britain and Argentina, pp. 45-49; and Lynch. ‘British Policy’, pp. 21-24.7. Castlereagh, Viscount, ‘Memorandum for the Cabinet, Relative to South America’, 1 May 1807,

in C.W. Vane, ed., Correspondence, Despatches, and Other Papers, of Viscount Castlereagh,Second Marquess of Londonderry, VII, London, 1851, p. 319.

8. Ibid., p. 320.9. Much was made of this document by Ferns, Britain and Argentina, pp. 46-48. Platt then used

Ferns’ selective quotations to criticise Gallagher and Robinson’s notion of the ‘imperialism offree trade’. D.C.M. Platt, ‘The Imperialism of Free Trade: Some Reservations’, EconomicHistory Review, 21:2, 1968, p. 299; cf. idem, ‘Further Objections to an ‘Imperialism of FreeTrade’, 1830-60’, Economic History Review, 26:1, 1973; and Gallagher and Robinson, ‘Imperial-ism of Free Trade’. The full quotation from Castlereagh’s memorandum is, however, far morecompatible with Robinson and Gallagher’s analysis than Platt realised.

10. Castlereagh, ‘Memorandum for the Cabinet’, p. 321, emphasis added.

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Castlereagh’s argument was reinforced shortly thereafter when another invasion of

Buenos Aires failed,11 leading to a decisive reorientation of British policy toward a

more informal kind of empire. From then on, not only in Spanish America but across

the periphery, formal colonisation would be avoided as long as there was a collabor-

ative elite – a ‘native force’ – to work with.12

The promise of improved terms of trade was the key to the initial formation

of a collaborative elite in the River Plate. Under the Spanish empire the terms of

trade had been depressed by the Spanish trade monopoly, which sought to channel

silver from the mines of Upper Peru to Spain for the benefit of the Spanish state.13

This system generated great price differentials between Europe and the Americas due

to the high trade costs that it entailed. Hence, even following substantial trade liberal-

isation in the eighteenth century, competition among Spanish merchants in Buenos

Aires remained minimal, so their markups were high.14 Moreover, their shipping was

inefficient, and their goods were heavily taxed – in both Spain and Buenos Aires – by

the Spanish authorities,15 which depressed export prices and inflated import prices in

11. Ferns, Britain and Argentina, pp. 37-45; and Gallo, Great Britain and Argentina, pp. 43-47.12. R. Robinson, ‘Non-European Foundations of European Imperialism: Sketch for a Theory of

Collaboration’, in R. Owen and B. Sutcliffe, eds., Studies in the Theory of Imperialism, London,1972, pp. 117-42; and idem, ‘The Excentric Idea of Imperialism, With or Without Empire’, in J.Osterhammel and W.J. Mommsen, eds. Imperialism and After: Continuities and Discontinuities,London, 1986. For a useful discussion of Robinson’s ‘peripheral’ theory of European imperial-ism, see Cain and Hopkins, British Imperialism, pp. 26-30.

13. The fiscal logic of the Spanish trade monopoly has often been missed, as economic historianshave instead seen it as intended to ‘build a rich and solid economy’ in Spain. G. Márquez,‘Commercial Monopolies and External Trade’, in V. Bulmer-Thomas, J. Coatsworth, and R.Cortés Conde, eds., The Cambridge History of Latin America, I, The Colonial Era and the ShortNineteenth Century, Cambridge, 2005, p. 397. In establishing the monopoly, however, thecrown’s principal goal was to finance its own war-making. Subsequently, the monopoly came toplay an important role in Spain’s fiscal system, as much of the crown’s revenues came fromtaxing American exports and imports when they passed through Spain, especially those colonialgoods that the crown itself imported. Moreover, by the late eighteenth century a disproportionateamount of its domestic revenues came from Cádiz, the region of Spain that benefited most fromthe trade monopoly. See J.A. Barbier and H.S. Klein, ‘Revolutionary Wars and Public Finance:The Madrid Treasury, 1784-1807’, Journal of Economic History, 41:2, 1981, pp. 327-28, 328-30;C. Marichal, ‘Beneficios y costes fiscales del colonialismo: Las remesas americanas a España,1760-1814’, Revista de Historia Económica, 15:3, 1997, p. 480; and J. Cuenca-Esteban, ‘WasSpain a Viable Fiscal-Military State on the Eve of the French Wars?’, in S. Conway and R. TorresSánchez, eds., The Spending of States: Military Expenditure During the Long EighteenthCentury: Patterns, Organisation, and Consequences, 1650-1815, Saarbrücken, 2011, pp. 247-56.

14. Socolow suggests that 70 percent was considered an ‘acceptable markup’. S.M. Socolow, TheMerchants of Buenos Aires, 1778-1810, Cambridge, 1978, p. 60.

15. Many goods imported from Spain came from other parts of Europe, so they were taxed whenthey entered Spain, taxed again when they were reexported, then taxed again upon arrival inBuenos Aires. The River Plate’s exports would pay the same taxes, although in the oppositeorder. Newland and Ortíz, ‘Economic Consequences’, pp. 276-78.

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the River Plate. Thus, in the first half of the 1790s cattle hides sold in Buenos Aires

for as little as 20 percent of their wholesale price in Cádiz.16 Ranchers accordingly

tended to be impoverished, with most illiterate and many lacking basic goods, such

as shoes and socks.17 When they heard of the greatly improved terms of trade that

British merchants were providing in Montevideo, the city across the River Plate estu-

ary that was occupied during the British invasions, they therefore lobbied the Spanish

authorities for trade liberalisation. Mariano Moreno, a prominent young lawyer,

famously appealed to the Spanish viceroy on their behalf.18 He noted that in

Montevideo ‘[s]ales were made at advantageous prices, goods were bought at

minimal values, and the rural world wore fabrics that it had never known before,

having sold at high values hides that its grandparents had thrown away as useless’.19

The ranchers and their representatives had recognised, then, that the terms of trade

had improved dramatically under the British, so they sought the end of the Spanish

trade monopoly, through independence if necessary.20

Spain’s trade monopoly ended with the disintegration of the empire. Already

in November 1809 the Spanish viceroy had been persuaded by Moreno and others to

allow two British merchants to disembark and sell their cargoes.21 Then, three days

after an independent government was declared in late May 1810, the remaining

restrictions on trade with foreigners were removed.22 Subsequently, the number of

merchants arriving rose: whereas 50 ships had docked per year at Buenos Aires in the

mid-1790s, before the French Wars began, there were over 250 foreign merchant

vessels entering annually by the early 1820s.23 Increased competition among

16. Amaral, Rise of Capitalism, p. 234, Table 11.1.17. C.A. Mayo, ‘Landed but not Powerful: The Colonial Estancieros of Buenos Aires (1750-1810)’,

Hispanic American Historical Review, 71:4, 1991, pp. 769-70; and idem, Estancia y sociedad enla Pampa 1740-1820, Buenos Aires, 1995, pp. 60-61.

18. Lynch, Spanish American Revolutions, pp. 49-50.19. D.M. Moreno, Representación que el apoderado de los hacendados de las campañas del Río de

la Plata, Buenos Aires, (1809) 1874, p. 29, author’s translation.20. As Adelman has stressed, independence in itself was not necessarily the goal of revolutionaries

such as Moreno. Rather, they sought trade liberalisation so that the country would be able toexploit its land resources. J. Adelman, Republic of Capital: Buenos Aires and the Legal Trans-formation of the Atlantic World, Stanford, 1999, ch. 3. On the failure of Spain to come to acompromise with the Latin American revolutionaries on this issue, see Costeloe, ‘Spain and theLatin American Wars’.

21. Lynch, Spanish American Revolutions, pp. 49-50.22. Ferns, Britain and Argentina, p. 65.23. Z. Moutoukias, ‘El crecimiento en una economía colonial de antiguo regimen: Reformismo y

sector externo en el Río de la Plata’, Arquivos do Centro Cultural Calouste Gulbenkian, 34,1995, p. 803, Table 2; and Llorca-Jaña, British Textile Trade, p. 341.

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merchants then turned Buenos Aires into more of a sellers’ market for pastoral produ-

cers and a buyer’s market for consumers of imported goods. Hence, in the early

1820s, a resident British merchant claimed to ‘have bought English stockings

cheaper than I could buy them in London’, and that it was ‘cheaper to purchase a

stock of linen [in Buenos Aires] than at home’.24 Furthermore, export duties were

lowered considerably,25 British and other foreign shipping was more efficient than

Spanish vessels, and merchants were no longer obliged to ship their goods via Spain,

so falling trade costs led to rapid price convergence: in the first half of the 1790s

hides had sold in Buenos Aires for around 20 percent of their CIF price in Britain,

but they were selling for 80-90 percent by the 1820s.26 The terms of trade would then

continue to improve thanks to the falling prices of the core’s manufactured goods, as

well as falling trade costs due to more efficient shipping, faster flows of information,

better packaging of goods, and more competition among merchants.27

The available price record confirms that Argentina experienced a massive

terms-of-trade boom during the long nineteenth century. As indicated by the findings

of Chapter 2, Argentina’s own prices should ideally be used to measure its terms of

trade. The price record is, however, fragmentary, so historians up to now have mainly

relied upon prices from European countries as proxies for prices in Argentina itself.28

24. An Englishman, A Five Years Residence in Buenos Ayres During the Years 1820 to 1825, 2nd ed.,London, 1827, p. 93.

25. Within two weeks of independence, export taxes would be lowered (Buenos Ayres, Gazeta, 1,1810, p. 6), and then they would be further eroded by inflation, falling to just four percent on dryox hides by the end of the 1820s. Calculated from J. Broide, ‘La evolución de los precios pecuar-ios argentinos en el periodo 1830-1850’, mimeo, 1951, p. 41, Cuadro 16; also published inRevista de la Facultad de Ciencias Económicas, 4:32, pp. 113-83; and M.A. Irigoin, ‘Finance,Politics and Economics in Buenos Aires, 1820s-1860s: The Political Economy of Currency Stab-ilisation’, PhD diss., University of London, 2000, p. 126, Table II.1.6. Export taxes were erodedby inflation because, from 1822 onward, they were in fixed paper money amounts that were onlysporadically adjusted for rising prices. See ibid., pp. 129-30.

26. Calculated from the price data in Tables DA.12-DA.14. For discussion of the hide price data, seeAppendix 4.1, pages 176-81. The differential varies according to which series of hide prices inBritain is used.

27. For evidence of these process specific to the River Plate, see D.C.M. Platt, Latin America andBritish Trade 1806-1914, London, 1972, p. 14; J.E. Oribe Stemmer, ‘Freight Rates in the Tradebetween Europe and South America, 1840-1914’, Journal of Latin American Studies, 21:1, 1989,pp. 23-59; Y. Kaukiainen, ‘Shrinking the World: Improvements in the Speed of InformationTransmission, c. 1820–1870’, European Review of Economic History, 5:1, 2001, pp. 5, 20, Tables1 and 4; and Llorca-Jaña, British Textile Trade, ch. 7.

28. For example, Newland, ‘Exports and Terms of Trade’; and Llorca-Jaña, British Textile Trade, p.195, Figure 7.4. As noted in the introduction, this is still preferable to those works that havelooked just at the prices of Argentina’s exports in foreign countries, without deflating them. Mostnotably, Halperín Donghi, ‘Expansión ganadera’, pp. 62-66.

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Typically this has produced estimates that imply an improvement in the terms of

trade of at most 200 percent from 1810 to 1913.29 A careful reconstruction of the

existing price record nevertheless suggests that this is a significant underestimate.

Figure 4.1 illustrates this using the domestic wholesale prices of nine of the country’s

main exports, which were compiled for this dissertation from various sources, as will

be described at length in Appendix 4.1.30 They are here shown relative to a crude

proxy import price index that consists of the export prices of six of Argentina’s major

trade partners,31 with the result indicating a far greater terms-of-trade boom than is

normally supposed. Indeed, when all the series are indexed to make a ‘part-proxy’

estimate of Argentina’s terms of trade, as in Figure 4.2, they show an improvement of

1,700 percent from the 1780s to the 1900s, and even this is likely to be an under-

estimate due to the downward bias in the trend in part-proxy estimates for the nine-

teenth century.32 If adjustments are made for the effects of falling trade costs on

import prices, it seems likely that the improvement would be more than 2,000

percent over the same period. Assuming, for instance, that the differential of import

prices in Argentina to export prices in the core fell from 100 percent in the 1780s to

20 percent in the 1900s, which is plausible, the terms of trade would have improved

by 2,500 percent.33 What is more, the terms of trade also appear to have become

29. For example, Ferreres, Dos siglos, Table 8.1.7. The sources used by Ferreres are substantially thesame as those of Williamson, as previously discussed in Appendix 2.1, page 87: Newland,‘Exports and Terms of Trade’; and Ford, ‘Export Price Indices’; via di Tella and Zymelman,Etapas del desarrollo, p. 56, Table 10.

30. To preempt Appendix 4.1, the sources used were Anon., ‘Report on the Trade of the River Plate’,reproduced in R.A. Humphreys, British Consular Reports on the Trade and Politics of LatinAmerica 1824-26, London, (1824) 1940, p. 33; idem, ‘Precios corrientes de productos en BuenosAires en los años 1821, 1822 y 1823’, in E.M. Barba, ed., Informes sobre el comercio exterior deBuenos Aires durante el gobierno de Martín Rodríguez, Buenos Aires, (1824) 1978, p. 60;DGEN, Extracto estadístico de la República Argentina correspondiente al año 1915, BuenosAires, 1916, pp. 204-17; A. Bunge, Intercambio económico de la República, 1910-1917, BuenosAires, 1919, ch. 11; Álvarez, Temas de historia, pp. 208-26; Broide, ‘Evolución de los precios’,pp. 41-43, 50, Cuadros 16-18, and 22; R. Cortés Conde, T. Halperin Donghi, and H. Gorosteguide Torres, ‘Evolución del comercio exterior argentino: Tomo I Exportaciones: Parte primera1864-1930’, mimeo, 1965, pp. 73-79; V. Vázquez-Presedo, Estadísticas históricas argentinas(comparadas), II, Segunda parte 1914-1939, Buenos Aires, 1971, pp. 194-221; and Moutoukias,‘Crecimiento en una economía’, p. 804, Cuadro 3.

31. The use of such a proxy index is crude because it assumes that the composition of Argentina’simports from each of the six countries was similar to the composition of their exports to all coun-tries. Nevertheless, it is still preferable to the common practice of just using Britain’s exportprices as a proxy for a peripheral country’s import prices (see Chapter 2). How the six countries’export prices were indexed will be detailed in Appendix 4.1, pages 187-88.

32. On the downward bias in part-proxy estimates, see Chapter 2, pages 64-80.33. See Appendix 4.1, pages 189-92.

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Figure 4.1Part-Proxy Terms of Trade for Nine Argentine Exports, 1780-1913

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Hides, dried (1780+)

1913 = 100

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Hides, salted (1821+)

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Jerked beef (1829+)

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Tallow (1833+)

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Wool (1833+)

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Figure 4.1 (cont.)Part-Proxy Terms of Trade for Nine Argentine Exports, 1780-1913

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Cattle* (1864+)

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Wheat (1878+)

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Maize (1879+)

0

50

100

150

200

1780 1800 1820 1840 1860 1880 1900 1920

Linseed (1887+)

* Also used as a proxy for chilled and frozen beef in the export price index.

Note: The wholesale price of each good in Buenos Aires was divided by a chained, geometricLaspeyres index of the export prices of Argentina’s major trade partners, then all series werereferenced so that 1913 equalled 100. The trade partners included in the proxy import priceindex are Britain (from 1780), the United States (from 1790), France (from 1809), Brazil(from 1821), Italy (from 1862), and Germany (from 1880).

Sources: See Appendix 4.1. The underlying series are reproduced in Tables DA.13-DA.17 inthe Data Appendix.

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Figure 4.2Part-Proxy Terms of Trade for Argentina, 1780-1913

0

20

40

60

80

100

120

1780 1800 1820 1840 1860 1880 1900 1920

1913 = 100

Note: The series is a chained, geometric Laspeyres index, calculated from the nine series inFigure 4.1, together with series for sheep skins (1864+), flour (1880+), goat skins (1893+),and numerous other minor exports from 1910 onward.

Sources: See Appendix 4.1. The underlying series are reproduced in Tables DA.13-DA.17 inthe Data Appendix.

increasingly stable, as indicated by the two measures of volatility shown in Figure

4.3. Panel (a) simply shows the annual percentage change in the series; Panel (b)

shows the cyclical component in the series as a percentage of its trend component.

Both suggest decreasing volatility.34 The impact of British expansion had thus

triggered an unprecedented terms-of-trade boom in the River Plate, during which the

terms of trade improved persistently for over a century, while also becoming less

volatile. In time, this long boom would generate the kind of ‘native force’ imagined

by Castlereagh, as global capitalism, through the terms of trade, reordered the River

Plate.

34. Some caution should be exercised in interpreting the strong volatility during the 1810s becausethe source for the export price index for this period is based on hide prices that are given asseveral-year averages (from anon., ‘Report on the Trade’, p. 33). Nonetheless, even if the 1810swere excluded from the picture, the impression of declining volatility would remain.

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Figure 4.3Volatility in Argentina’s Part-Proxy Terms of Trade, 1780-1913

-60

-40

-20

0

20

40

60

1780 1800 1820 1840 1860 1880 1900 1920

(a) Annual % change

-60

-40

-20

0

20

40

60

1780 1800 1820 1840 1860 1880 1900 1920

(b) % variation from trend*

* The cyclical component as a percentage of the trend component. Both were calculated usinga Hodrick-Prescott Filter, with the smoothing parameter set at 1,000.

Sources: Calculated from the series in Figure 4.2.

Native ForcesThe long terms-of-trade boom radically changed the incentives that people faced.

The rest of this chapter outlines that process and its results. It first argues, following

Burgin,35 that the long boom drove River Plate’s descent into civil war after inde-

pendence because of its uneven impacts on land-abundant and land-scarce regions.

Whereas improved terms of trade allowed the Littoral to prosper thanks to its vast

land resources and river system, they made the more densely populated and/or land-

locked interior stagnate.36 The conflicts generated by these opposite paths then

prevented the formation of a unified state, as the interior’s Federalists sought provin-

cial autonomy, in order to protect their cottage industries from the influx of cheap

imports, while landowners in the Littoral opposed a unified state since they did not

35. Burgin, Economic Aspects, ch. 1.36. As noted in Chapter 1, page 31, footnote 85, Argentina’s North and West are Andean regions with

similar land resources to Bolivia. The centre of the country has vast plains of Pampean land, butdoes not have a river system to connect it to the sea.

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wish to see Buenos Aires City made a federal capital, juridically separate from its

rural hinterland.37 Only massive injections of British capital, attracted to the country

by its ongoing terms-of-trade boom, allowed these conflicts to be resolved, as a Brit-

ish-financed network augmented the federal government’s capacity to intervene in

favour of its supporters in the provinces, while also giving the provincial ruling

classes the opportunity to profit from the expansion that was taking place in the Litt-

oral. From this perspective, then, state formation in Argentina was not inevitable,38

since it was highly contingent upon developments in the global political economy.

Moreover, the impression given in the existing literature of the state being pulled

outward from Buenos Aires is also misleading because the federal government was

effectively pulled into the interior by elements of the provincial ruling classes.39 For

this reason, when it formed, Argentina’s state would be an oligarchic state, heavily

influenced by the power structures of the most backward parts of the country, which

had lost out from the long boom.

The Civil WarsIn 1820s it appeared that Castlereagh’s collaborative elite had already formed. Bern-

ardino Rivadavia was its most prominent representative. The creole (that is, Amer-

ican-born) son of a Spanish merchant and lawyer, Rivadavia’s rise to prominence

began when he participated in the militias that had repelled the British invasions; he

then went on to fight in the wars of independence against Spanish rule. In 1814 the

new government in Buenos Aires sent Rivadavia to Europe to drum up support for its

cause in London and Paris. During his six-year sojourn he would familiarise himself

with the emerging ideas of liberalism, particularly through the works of Jeremy

Bentham, with whom he corresponded. Upon his return to Argentina in 1821, Riva-

davia became the principal minister to Martín Rodríguez, the governor of Buenos

Aires Province, under whom he implemented reforms that were intended to win

diplomatic recognition from the British government and attract British capital. Riva-

37. In making this argument about Buenos Aires’ landowners, this chapter draws on K.M. Monsma,‘Ranchers, Rural People, and the State in Post-Colonial Argentina’, PhD diss., University ofMichigan, 1992, ch. 8.

38. As it often appears in Oszlak, Formación del estado, esp. 272-75.39. Again, as discussed in Chapter 1, pages 33-34, in making this point, this chapter is inspired by de

la Fuente’s critique of Oszlak. See de la Fuente, Children of Facundo, p. 188; cf. Oszlak, Forma-ción del estado, esp. 272-75.

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davia, once a resistance fighter against British domination, had thus become the

River Plate’s main collaborator.40

Predictably, the British merchants who had flocked to Buenos Aires following

independence profusely praised Rivadavia. In an 1824 report to Woodbine Parish, the

new British consul to Buenos Aires, the merchants credited the Rodriguez govern-

ment with having engineered a great increase in prosperity by promoting trade.41 On

that basis, Parish advised George Canning, the new Foreign Secretary, that ‘the bene-

fits of a good government, which has been at last established, are now quite suffi-

ciently known and understood to ensure the support of all classes of the people’.42 It

seemed, in other words, that, under British countenance, a suitable native force was

forming, so the next year the United Provinces of the River Plate were formally

recognised by the British government, consolidating their position as an independent

state.43

The River Plate soon descended, however, into civil war. In a constitutional

assembly begun in 1823 Rodríguez and Rivadavia had pushed for a unitary constitu-

tion for the new republic that would have established a strong central government in

Buenos Aires City, which was to be juridically separated from its surrounding

province. In doing so, the Unitarians antagonised the governors of the interior

provinces, who wished to retain their provincial militias, while they also provoked

the opposition of Buenos Aires’ landowners, who did not wish to see their rural land-

holdings separated from the city. Consequently, having been appointed president

under the new unitary constitution in 1826, Rivadavia was forced to resign just a year

later. His successor, Manuel Dorrego, annulled the new constitution, but was

executed in 1828, following a military coup led by Juan Lavalle, a Unitarian army

officer. Frontier militias led by Juan Manuel de Rosas, a major landowner, together

with the forces of Estanislao López, the governor of Santa Fe, then besieged Buenos

Aires to dislodge Lavalle, which they succeeded in doing in 1829. Rosas was then

made governor of Buenos Aires, with the provincial assembly granting him

extraordinary powers to rule as a dictator until order was restored – powers which he

40. See K. Gallo, The Struggle for an Enlightened Republic: Buenos Aires and Rivadavia, London,2006.

41. Anon., ‘Report on the Trade’, p. 34.42. Quoted in Gallo, Great Britain and Argentina, p. 142.43. Gallo, Great Britain and Argentina, ch. 6; cf. Ferns, Britain and Argentina, ch. 4.

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continued to use as governor for much of the 1830s and all of the 1840s. Rosas

became the de facto leader of the Argentine Confederation, which functioned as a

loose alliance of autonomous provinces, with Buenos Aires given control of foreign

policy.44

To understand why Argentina fragmented, it is necessary consider the River

Plate’s development up to independence. Prior to colonisation in the sixteenth

century, the mountainous interior had been populated by sedentary agriculturalists,

living on the southern periphery of the Incan empire. Spanish settlers rapidly establ-

ished themselves as overlords of the Andean peasant populations, using Indian labour

to supply Potosí, the great mining city in Upper Peru. They provided it with mules,

sugar, wine, and tobacco, the production of which was protected by the high trade

costs that resulted from the Spanish trade monopoly. All goods legally imported from

Europe had to be shipped from Seville (and later Cádiz) to the Isthmus of Panama,

carried across land to the Pacific, shipped to Callao, Lima’s Pacific port, then taken

4,000 kilometres overland in mule trains to the River Plate. Such a lengthy journey

brought high trade costs, which inflated the prices of imports, thereby providing a

considerable degree of protection for the Andean peasants’ industries. In the Littoral

region, meanwhile, Buenos Aires developed as an entrepôt for a flourishing contra-

band trade, with imports of slaves, European manufactures, and tropical goods from

Brazil illicitly exchanged for silver from Upper Peru.45

In the eighteenth century trade was gradually liberalised, especially once

Buenos Aires was made the capital of a new Viceroyalty of the River Plate in 1776,

after which free trade with Spain was permitted. Buenos Aires, moreover, was given

control over Potosí, so its treasury became the recipient of large fiscal transfers from

the treasury of the mining region.46 Greater government expenditure then increased

44. See J. Lynch, Argentine Dictator: Juan Manuel de Rosas 1829-1852, Oxford, 1981, pp. 31-43.;and J.C. Chiaramonte, ‘El federalismo argentino en la primera mitad del siglo XIX’, in M.Carmagnani, ed., Federalismos latinoamericanos: México, Brasil y Argentina, México, DF,1993, pp. 91-93. On the constitutional basis of Rosas’ rule, see idem, ‘The ‘Ancient Constitution’after Independence (1808–1852)’, Hispanic American Historical Review, 90:3, 2010, pp. 455-88.

45. See Halperín Donghi, Politics, Economics, pp. 6-16; Brown, Socioeconomic History, pp. 9-25; E.Tandeter, ‘El eje Potosí-Buenos Aires en el imperio español’, in M. Ganci and R. Romano, eds.,Governare il mondo: L’imperio spagnolo dal XV al XIX secolo, Palermo, 1991, pp. 185-94; andZ. Moutoukias, ‘Comercio y producción’, in Academia Nacional de Historia, ed., Nueva historiade la Nación Argentina, IV, Buenos Aires, 2000, pp. 72-81.

46. See Brown, Socioeconomic History, ch. 2; Tandeter, ‘El eje Potosí-Buenos Aires’, pp. 194-201;Moutoukias, ‘Crecimiento en una economía’; and idem, ‘Comercio y producción’, pp. 81-92.

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demand for imported goods, which Spanish merchants provided, taking Potosí’s

silver as payment and remitting it back to Spain.47 The terms of trade probably

improved somewhat during this period,48 although they still remained depressed

because of the lack of competition among the Spanish merchants, their inefficient

shipping, and the numerous taxes that were imposed on their goods in Spain and

Buenos Aires.49

In the Littoral region the terms-of-trade boom that began after independence

sparked an expansion in exports, leading to staple theory-style extensive growth.50

The Robertson brothers, two prominent Scottish merchants, provided a vivid account

of how they spurred growth in Corrientes, a Littoral province, in the 1810s.51 When

the Robertsons arrived, they found that the region’s ranchers ‘paid high prices for

their goods, and got low ones for their produce’52 – their terms of trade were, in other

47. Bizarrely, such flows of silver from treasuries in mining regions to the treasuries of ports havebeen taken as evidence that the Spanish imperial system ‘successfully aimed at making the colon-ies self-sufficient, with intra-colonial transfers covering the needs of regions that either could notor would not raise sufficient revenue’. R. Grafe and M.A. Irigoin, ‘The Spanish Empire and ItsLegacy: Fiscal Redistribution and Political Conflict in Colonial and Post-Colonial Spanish Amer-ica’, Journal of Global History, 1:2, 2006, p. 263; cf. idem, ‘Bargaining for Absolutism: A Span-ish Path to Nation-State and Empire Building’, Hispanic American Historical Review, 88:2,2008. This argument seems oblivious to the fiscal role of the trade monopoly, as it ignores thenumerous taxes imposed on exports and imports in Spain, as well as the tax revenues it generatedin Cádiz. Once this aspect of the trade monopoly is taken into consideration, channeling silverfrom mining regions to the ports can be seen as a means to increase the crown’s revenues byensuring that the silver would be used to purchase imports form Spain; it was not an attempt atcolonial developmentalism. On the imperial fiscal system, see page 129, footnote 13.

48. The price record is, unfortunately, extremely fragmentary. There are prices of cattle, but few onthe prices of hides. See J.C. Garavaglia, ‘Precios de los productos rurales y precios de la tierra enla campeña de Buenos Aires: 1750-1826’, Boletín del Instituto de Historia Argentina y Americ-ana ‘Dr. Emilio Ravignani’, 3:11, 1995; and Moutoukias, ‘Crecimiento en una economía’. Theprices of some imported goods are available from Johnson, ‘Salarios, precios’, with the dataonline at http://gpih.ucdavis.edu/files/Buenos_Aires_1770-1812.xls (accessed 6 October 2013);and M. Cuesta, Precios, población, impuestos y producción: La economía de Buenos Aires en elsiglo XVIII, Buenos Aires, 2009, with the data online at http://gpih.ucdavis.edu/files/Buenos_Aires_1700-1800.xls (accessed 6 October 2013). These prices suggest that there wassome improvement in the terms of trade, but it was minimal compared to what would happenafter independence. Thus, from the first decade of the eighteenth century to the last, the price of acow increased by around 230 percent relative to both wine and paper, and by about 100 percentrelative to wood.

49. Newland and Ortíz, ‘Economic Consequences’, pp. 276-78.50. The classic application of staple theory to the Littoral in this period is Brown, Socioeconomic

History, chs. 3-7.51. J.P. Robertson and W.P. Robertson, Letters on South America: Comprising Travels on the Banks

of the Paraná and Rio de la Plata, I, London, 1843. On the Robertsons, see Halperín Donghi,Politics, Economics, pp. 87-88; V.B. Reber, British Mercantile Houses in Buenos Aires,1810-1880, Cambridge, MA, 1979, pp. 112-13; and R.D. Salvatore, ‘The Breakdown of SocialDiscipline in the Banda Oriental and the Littoral, 1790-1820’, in M.D. Szuchman and J.C.Brown, eds., Revolution and Restoration: The Rearrangement of Power in Argentina 1860,Lincoln, NE, 1994, pp. 90-95.

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words, depressed. According to their own account, the Robertsons transformed that

situation by reversing ‘the plan of the Old Spaniards: we gave high prices for hides,

and took low ones for goods’.53 They described the result as follows:

[T]he country, as if by magic, started into industrious life and mercantile activity, inevery section of its wide extent. Herds and flocks were gathered together, – thou-sands and tens of thousands of the wild cattle were slaughtered for their hides; andin all directions the creaking of the large wheels of huge and ponderous wagons,laden with the produce of the estancias and villages, as they uninterruptedlytraversed the country, gave token of renewed prosperity and peace, where a fewmonths, nay a few weeks, before, all had been rapine, desolation, and decay.54

Such optimism reflected the experience of the Littoral provinces because they were

able to take advantage of the terms-of-trade boom due to the navigable rivers that

connected them to the oceans, which meant they could export their produce.

Buenos Aires, in particular, had a uniquely privileged position, not only

because there were roughly 400,000 square kilometres of Pampas grasslands to its

south and west,55 but also due to the city’s strategic location on the River Plate estu-

ary, which allowed it to monopolise the customshouse revenues that came from

taxing overseas trade. By the end of the 1820s, the customshouse was providing

around 80 percent of revenues,56 giving Buenos Aires vastly greater fiscal resources

than the other provinces.57 To increase these revenues, the government encouraged

the expansion of ranching, thereby beginning a long-term commitment to promoting

the export sector.58 Land grants had already been made soon after independence to

52. Robertson and Robertson, Letters on South America, pp. 174-7553. Ibid., pp. 176-7754. Ibid., p. 179.55. Cortés Conde, Progreso argentino, p. 56, Cuadro 2.1.56. T. Halperín Donghi, Guerra y finanzas en los origenes del Estado argentino (1791-1850),

Buenos Aires, (1982) 2005, pp. 175-77.57. In the 1820s, Buenos Aires’s revenues per capita were roughly four times those of Corrientes,

five times those of Entre Ríos, 11 times those of Mendoza, 16 times those of Santa Fe, and 22times those of Tucumán. Revenues from ibid., pp. 169, 173, 177; and R. Cortés Conde, F.Converso, L. Coria, A.I. Ferreyra, and E.C. Schaller, ‘Las finanzas públicas y la moneda en lasprovincias del interior (1810-1860)’, in Academia Naional de Historia, ed., Nueva historia de laNación Argentina, V, Buenos Aires, 2000, pp. 518, 521-24, Tables 3-7. An idea of the populationof each province can be gained by interpolating between estimates for 1809 and 1869 in J.Comadrán Ruiz, Evolución demográfica argentina durante el período hispano: 1535-1810,Buenos Aires, 1969, p. 115; and Superintendente del Censo, Primer censo de la RepúblicaArgentina, Buenos Aires, 1872, p. 633, Tabla 1. The population figures for 1809 are extremelyapproximate.

58. T. Halperín Donghi, ‘The Buenos Aires Landed Class and the Shape of Argentine Politics(1820-1930)’, in E. Huber and F. Safford, eds., Agrarian Structure & Political Power: Landlord& Peasant in the Making of Latin America, Pittsburgh, 1995, pp. 44-45.

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encourage ranchers to push Buenos Aires’ frontiers into Indian territory,59 and in the

1820s large tracts of Pampean land, which was mostly publicly owned, became avail-

able on 20-year, transferable leaseholds, most of which would later be converted to

freehold titles under Rosas in the 1830s.60 A new landowning class would then

become the principal beneficiary of the export expansion that began in the 1840s.61

Cattle hides accounted for most of the growth, although jerked beef, other skins and

hides, tallow, and increasingly wool also became important exports. Initially, these

pastoral goods mainly went to Britain, but continental Europe and the United States

subsequently became the major importers.62

The interior provinces, where approximately two thirds of the population

lived at independence,63 were less fortunate because a relative scarcity of land and/or

high internal transportation costs largely excluded them from the benefits of the long

boom.64 Córdoba, most notably, was an interior province that had an abundance of

Pampas land, but it could not bring it into production for export because it was land-

locked. Hence, in the 1830s and ‘40s just two percent of hides exported from Buenos

59. Cárcano, Evolución histórica, ch. 3; and M.E. Infesta, ‘Aportes para el estudio del poblamientode la frontera del Salado’, in Archivo Histórico de la Provincia de Buenos Aires, ed., Estudiossobre la Provincia de Buenos Aires, La Plata, 1991.

60. M.E. Infesta, ‘La enfiteusis en Buenos Aires, 1820-1850’, in S. Amaral and M. Valencia, eds.,Argentina: El país puevo: Problemas de historian económica, 1800-1914, La Plata, 1999; andidem, La pampa criolla: Usufructo y apropiación privada de tierras públicas en Buenos Aires,1820-1850, Mar del Plata, 2006.

61. The historiography on the rise of Argentina’s landowning class has been heavily influenced byHalperín Donghi. See R.O. Fradkin, ‘Tulio Halperin Donghi y la formación de la clase terrateni-ente porteña’, in R. Hora, and J. Trímboli, eds., Discutir Halperin: Siete ensayos sobre lacontribución de Tulio Halperin Donghi a la historia argentina, Buenos Aires, 1997. Unable tosee any price incentive for its formation, Halperín Donghi concluded that Argentina’s capitalistsmust have begun to invest in land because the British forced them out of commerce. See HalperínDonghi, ‘Expansion ganadera’, pp. 72-73; and idem, ‘The Buenos Aires Landed Class’, p. 42.The problem with this argument is that both creole and Spanish merchants remained heavilyinvolved in trade long after independence. K. Robinson, ‘The Merchants of Post-IndependenceBuenos Aires’, in M.L. Moorhead and W.S. Coker, eds., Hispanic-American Essays in Honor ofMax Leon Moorhead, Pensacola, 1979. As an alternative explanation, which again, followingHalperín Donghi, assumed there was no terms-of-trade boom, Amaral suggested that the rise ofthe landowners was due to the institution of the estancia. Amaral, Rise of Capitalism, esp. ch. 1.Irigoin then argued that capitalists invested in land as a hedge against inflation. A. Irigoin,‘Inconvertible Paper Money, Inflation and Economic Performance in Early Nineteenth CenturyArgentina’, Journal of Latin American Studies, 32:2, 2000, pp. 333-59. Such explanations never-theless become unnecessary once the extent of the terms-of-trade boom is recognised.

62. Amaral, Rise of Capitalism, ch. 12; and M.A. Rosal and R. Schmit, ‘Del reformismo colonialborbónico al libre comercio: Las exportaciones pecuarias del Río de la Plata (1768-1854)’,Boletín del Instituto de Historia Argentina y Americana ‘Dr Emilio Ravignani’, 3:20, 1999.

63. Again, this is an approximation, and does not include the indigenous populations beyond thefrontiers. Comadrán Ruiz, Evolución demográfica, p. 115.

64. Brown, Socioeconomic History, ch. 8. Even this optimistic take fails to find prosperity in theinterior.

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Aires originated from Córdoba, compared to around three quarters from Buenos

Aires itself, with the remainder coming from the other Littoral provinces.65 What

hides Córdoba did export were a byproduct of its own consumption of meat, given

that it was not worth slaughtering cattle for their hides alone.66 For similar reasons,

other interior provinces found that their products struggled to compete with cheaper

imports in the Littoral’s expanding market. In 1825, for example, it was estimated

that at a distance of 1,040 km the cost of transporting wine overland to Buenos Aires

equalled half the price of wine in that city.67 For distant wine-producing regions such

as Mendoza or San Juan, both around 1,000 km away from Buenos Aires, such high

transportation costs meant that their wines struggled to compete in the Littoral’s

market.68 Worse still, the interior’s textiles, which were mainly produced by peasant

women, not only lost their place in the Littoral’s market to imports,69 but were also

threatened by the cheap machine-produced goods being imported from Europe into

Buenos Aires and then reexported to other provinces.70 Federalist strongmen (caudil-

los) in the interior therefore sought to maintain their autonomy from Buenos Aires to

protect the cottage industries of the peasantries that formed their power base.71

65. Calculated from Rosal and Schmit, ‘Del reformismo colonial’, p. 101, Gráfico 6.66. Assadourian, Sistema de la economía, p. 238-39.67. Burgin, Economic Aspects, p. 118, Table 17. Conversion factor from leagues to kilometres from

Tornquist, Economic Development, p. 326.68. This analysis has been disputed by S. Amaral, ‘Free Trade and Regional Economies: San Juan

and Mendoza, 1780-1820’, in Szuchman and Brown, eds., Revolution and Restoration. Amaralargues that it was actually the civil wars that destroyed the West’s wine industry after independ-ence, rather than competition with foreign imports, and that it then took decades for grapeproduction to recover ‘because of its slower rhythms’ (‘Free Trade’, p. 144). It seems more likely,however, that competition with imports in the Littoral markets reduced profit margins, so vine-yards were converted to alfalfa, in order to feed the cattle that were being exported from Córdobato Chile. B. Bragoni, ‘Condiciones y estímulos en la recuperación de una economía regional:Prácticas mercantiles e instituciones empresarias en Mendoza, 1820-1880’, in M.A. Irigoin andR. Schmit, eds., La desintegración de la economía colonial: Comercio y moneda en el interiordel espacio colonial (1800-1860), Buenos Aires, 2003, pp. 278-79.

69. Assadourian, Sistema de la economía, pp. 253-65; Garavaglia and Wentzel, ‘Un nuevo aporte’,pp. 227-36; Palomeque, ‘Esteros de Santiago’, pp. 40-43; and Romano, Economía, sociedad, pp.123-26, 162-65.

70. These imports could travel overland because they were less bulky than the export staples. Ontheir penetration into the interior, see C.S. Assadourian and S. Palomeque, ‘Las relacionesmercantiles de Córdoba (1800-1830): Desarticulación y desmonetización del mercado internocolonial en el nacimiento del espacio económico nacional’, in Irigoin and Schmit, eds., Desinteg-ración de la economía, pp. 177-79, 182-84.

71. Burgin, Economic Aspects, pp. 16-17, also pp. 134-36; also see the discussion in Chapter 1, pages31-32. On the power base of the caudillos, see de la Fuente, Children of Facundo; and Paz,‘Province and Nation’, ch. 4. If foreign textiles had been allowed into the interior without restric-tions it would have increased underemployment among the rural poor, thereby lowering wages,which would have negated the welfare benefits of cheaper cloth.

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Within the Littoral too, the terms-of-trade boom generated powerful interests

that opposed the formation of a unified state. Whereas the colonial Spanish

merchants had shunned rural activities,72 following independence, many merchants

responded to improved terms of trade by investing in rural assets, while remaining an

essentially urban elite.73 The Anchorena family was the most successful.74 They

began as merchants enjoying the protection of the Spanish trade monopoly, but then

adapted rapidly to its abolition by establishing themselves as middlemen for British

and other foreign merchants. From the late 1810s they invested much of their profits

in land, but remained residents of the city, where they also participated in politics. In

the first half of the 1820s the Anchorenas, together with Rosas, their cousin and

ranch manager, led the opposition to Rivadavia’s attempt to create a unitary state

since they did not wish to see their city juridically separated from the countryside.

Many of those who actually lived in the countryside, by contrast, wished Buenos

Aires City to be federalised because the decisions of local magistrates (justices of the

peace) could only be appealed in courts in the capital, which gave absentee landown-

ers such as the Anchorenas a major advantage, as they lived in the city, where they

enjoyed considerable influence over the legal system. The Anchorenas for this reason

opposed a unitary state, as federalising Buenos Aires would have risked having

magistrates in the countryside who responded more to rural society, rather than to

urban capitalists such as themselves.75

The long boom thus disordered the River Plate by generating opposition to a

unitary state in both the interior and the Littoral. In the land-scarce and/or landlocked

interior, strongmen sought to maintain provincial autonomy to protect their peasant-

ries from the influx of cheaper imports, while the Littoral’s absentee landowners

were opposed to the formation of a unified state because it might weaken their influ-

72. Socolow, Merchants of Buenos Aires, p. 65.73. The results of this transformation are described in R. Hora, ‘El perfil económico de la elite de

Buenos Aires en las décadas centrales del siglo XIX’, Revista de Historia Económica, 24:2,2006. Also see D. Hernando, ‘Casa y Familia: Spatial Biographies in 19th Century BuenosAires’, PhD diss., University of California, 1973, pp. 30-34; D. Balmori, S.F. Voss, and M. Wort-man, Notable Family Networks in Latin America, Chicago, 1984, pp. 138-40; Monsma, ‘Ranch-ers, Rural People’, pp. 74-78; J. Gelman and D. Santilli, De Rivadavia a Rosas: Desigualdad ycrecimiento económico, Buenos Aires, 2006, ch. 4; and Losada, Historia de las élites, pp. 89-93.

74. See Brown, Socioeconomic History, ch. 8; R. Hora, ‘Del comercio a la tierra y más alla: Losnegocios de Juan José y Nicolás de Anchorena (1810-1856)’, Desarrollo Económico, 44:176,2005; and idem, ‘Los Anchorena: Patrones de inversión, fortuna y negocios (1760-1950)’,América Latina en la Historia Económica, 19:1, 2012.

75. Monsma, ‘Ranchers, Rural People’, ch. 8.

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ence in the countryside. Rosas formed a bridge between these two interests by using

the revenues given by the customshouse in Buenos Aires to subsidise his federalist

allies in the other provinces.76 Within Buenos Aires, meanwhile, he used the revenues

to build a highly militarised state77 – one in every four or five of the province’s adult

male population was in arms by the late 1830s.78 He used it to shape a new social

order for the benefit of the urban capitalists that supported him: the long-term lease-

holds of public land were privatised;79 he sought to regulate rural markets so that

only hides that came from the animals of titled landowners could be sold, thereby

excluding the hides of wild or rustled cattle killed by gauchos or Indians;80 gauchos

were, moreover, supposed to show a certificate of employment by a titled landowner

to avoid conscription into the army, turning them into wage labourers on ranches.81

Such policies helped make the distribution of wealth markedly more unequal under

Rosas,82 with Nicolás Anchorena, the family patriarch, becoming the richest man in

the country, its most important absentee landowner.83

Unitarianism could only regain the upper hand thanks to foreign intervention.

Rosas’ weakness was a vulnerability to the blockades that were occasionally imposed

by foreign powers, especially in response to his involvement in Uruguay’s civil wars.

First France blockaded Buenos Aires in the late 1830s, then Britain and France

76. See, for example, the case of Rosas’ ally Estansilao López in Santa Fe. J.C. Chiaramonte, G.E.Cussianovich, and S. Tedeschi de Brunet, ‘Finanzas públicas y política interprovincial: Santa Fey su dependencia de Buenos Aires en tiempos de Estanislao López’, Boletín del Instituto deHistoria Argentina y Americana ‘Dr. Emilio Ravignani’, 8, 1993.

77. Lynch, Argentine Dictator, ch. 5.78. J.C. Garavaglia, ‘La apoteosis del Leviathan: El estado en Buenos Aires durante la primera mitad

del XIX’ Latin American Research Review, 38:1, 2003, pp. 154-55.79. Infesta, Pampa criolla, pp. 97-110.80. K.L. Jones, ‘Warfare, Reorganization, and Readaptation at the Margins of Spanish Rule: The

Southern Margin (1573-1882)’, in F. Salomon and S.B. Shwartz, eds., The Cambridge History ofthe Native Peoples of the Americas, III:2, South America, Cambridge, 1999, pp. 173-5; and R.D.Salvatore, Wandering Paysanos: State Order and Subaltern Experience in Buenos Aires Duringthe Rosas Era, Durham, NC, 2003, pp. 38-9.

81. R.W. Slatta, Gauchos and the Vanishing Frontier, Lincoln, NE, 1983, pp. 111-12; R. Salvatore,‘Reclutamiento militar, disciplinamiento y proletarianización en la era de Rosas’, Boletín delInstituto de Historia Argentina y Americana ‘Dr Emilio Ravignani’, 3:5, 1992; and J.C. Gara-vaglia, ‘Paz, orden y trabajo en la campaña: La justicia rural y los juzgados de paz en BuenosAires, 1830-1852’, Desarrollo Económico, 37:146, 1997.

82. One estimate based on probate inventories resulted in a Gini coefficient that fell from 0.71 in1800 to 0.61 in 1829-30, but then rose again under Rosas to 0.80 in 1855-56. L.L. Johnson,‘Distribution of Wealth in Nineteenth-Century Buenos Aires Province: The Issue of Social Justicein a Changing Economy’, in K.J. Andrien and L.L. Johnson, eds., The Political Economy ofSpanish America in the Age of Revolution, 1750-1850, Albuquerque, 1994, p. 204, Table 2.

83. Hora, ‘Perfil económico’, p. 303.

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blockaded it together during the second half of the 1840s. These blockades not only

sabotaged state finances in Buenos Aires by reducing customshouse revenues, but

they also made the terms of trade deteriorate dramatically, which undermined support

for Rosas among the landowners. In 1839, in the midst of the French blockade, there

was an uprising against him among the smaller, rural landowners in the south of the

province.84 From then on, his state became more terroristic, with paramilitary groups

used to assassinate his enemies. Few supported him, therefore, when a Brazilian

army, aided by forces from Entre Rios, invaded Buenos Aires in 1852, defeating

Rosas at the Battle of Caseros.85 After Caseros, a unified state would slowly emerge.

The Oligarchic StateThe liberal intellectuals who had lived in exile under Rosas saw a railway network as

a key to state building.86 Juan Bautista Alberdi, for instance, believed that railways

would unite the newly prosperous Littoral with the populations of the interior, which

he saw as relics of Spanish colonialism. He wrote:

The railway is the means to put right what colonising Spain did back to front in thiscontinent. She placed the heads of our States where their feet should have been.According to the Spanish vision of isolation and monopoly, this system was wise;for our vision of expansion and free trade, it is fatal. The seats of power must bebrought to the coasts, or the Littoral taken to the continent’s interior. The railwayand the electric telegraph, these are the suppression of space, they perform thismarvel better than all the earth’s potentates. The railway innovates, reforms, andchanges the most difficult things, without decrees nor uprisings.87

Crucially, Alberdi believed, a railway network would allow a central government to

control the whole territory of Argentina, thereby bringing political unity. He

84. Halperín Donghi, Guerra y finanzas, pp. 141-42; idem, ‘Bloqueos, emisiones monetarias yprecios el Buenos Aires rosista (1838-1850)’, in F. Miró Quesada, F. Pease, and D. Sobrevilla,eds., Historia: Problema y promesa, Lima, 1978; and J. Gelman, Rosas bajo fuego: Losfranceses, Lavalle y la rebelión de los estancieros, Buenos Aires, 2009, ch. 2. Foreign historianshave often ignored these internal impacts of the blockades. For example, Ferns, Britain andArgentina, ch. 9; and D. McClean, War, Diplomacy and Informal Empire: Britain and the Repub-lics of La Plata, London, 1995, ch. 13.

85. Lynch, Argentine Dictator, chs. 6 and 8.86. On the ‘Generation of 1837’, see Shumway, Invention of Argentina, chs. 5-7; and Losada,

Historia de las elites, pp. 95-99. The role of railways in their thought is described in C.M. Lewis,British Railways in Argentina 1857-1914: A Case Study of Foreign Investment, London, 1983,pp. 6-8; and S.A. Palermo, ‘The Nation Building Mission: The State-Owned Railways in ModernArgentina, 1870-1930’, PhD diss., State University of New York, 2001, pp. 30-53.

87. J.B. Alberdi, Bases y puntos de partida para la organización política de la República Argentina,revised ed., Buenos Aires, 1915, pp. 96-97, author’s translation.

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continued:

Without the railway you will not have political unity in countries where distancemakes it impossible to assert central authority. You want, for example, the govern-ment, the legislators, and tribunals of the Littoral’s capital to legislate and judge theaffairs of the provinces of San Juan and Mendoza? Then bring the Littoral to theseplaces via the railway, or vice versa; at least put these extremities at three days’distance. But to have the metropolis or capital at 20 days’ journey is little better thanhaving it in Spain [...]. Therefore, political unity must begin with territorial integrity,and only the railway can make two places separated by 500 leagues one singleplace.88

Alberdi concluded that foreign capital was necessary to construct such a railway

network because there were insufficient domestic savings to pay for such a major

infrastructure project.89 Consequently, the 1853 constitution, which Alberdi’s work

inspired, called for the new federal government to actively promote foreign invest-

ment in railways.90

British capital would finance most of Argentina’s railway network from the

1860s onwards.91 It was not only pulled into the country by the various subsidies and

incentives provided by the Argentine government,92 but also due to a growing interest

88. Ibid., p. 97, author’s translation.89. Ibid., p. 98. This point has been disputed by D.C.M. Platt, ‘Foreign Finance in Argentina for the

First Half-Century of Independence’, Journal of Latin American Studies, 15:1, 1983, pp. 41-45;also T. Gómez and J. Schvarzer, ‘Ferrocarriles, expansión agraria y distribución de la tierra: Losdebates de 1860’, J. Schvarzer, T. Gómez, and A. Regalsky, eds., Estudios sobre la Historia delos Ferrocarriles Argentinos (1857-1940), Buenos Aires, 2007. Platt is probably correct thatsavings were sufficient to construct a railway network in the Littoral, but they were insufficientto construct the kind of national network imagined by Alberdi. Cf. Ferns, Britain and Argentina,pp. 312-15.

90. Representantes del Pueblo de la Nación Argentina, ‘Constitución de 1853 con reformas de 1860’,reproduced in N.P. Sagüés, ed., Constituciones iberoamericanas: Argentina, México, DF, (1860)2006, p. 300, Article 67, Part 16.

91. Lewis, British Railways. At the end of the long nineteenth century, French capital would also beinvested in the railway network. See A.M. Regalsky, ‘Foreign Capital, Local Interests and Rail-way Development in Argentina: French Investments in Railways, 1900-1914’, Journal of LatinAmerican Studies, 21:3, 1989.

92. This aspect of the construction of the railway network has been much emphasised in the recentliterature. As one particularly bold statement puts it, ‘[t]he construction of the railway system inArgentina was the result of decisions taken locally, fundamentally by those who exercised polit-ical power in the country’. M. Justo López, ‘Los ferrocarriles argentinos durante la primera pres-idencia de Julio Argentino Roca’, Revista Cruz de Sur, 3:4, 2013, p. 113, author’s translation;also see C.M. Lewis, ‘‘Anglo-Criollo’ Rather than British: Early Investments in Argentinian Rail-ways and Utilities’, in J. Schvarzer, A. Regalsky, and T. Gómez, eds., Estudios sobre la Historiade los Ferrocarriles Argentinos (1857-1940), Buenos Aires, 2007; and A.M. Regalsky, ‘Políticaspúblicas, capital extranjero y estructura de mercado: El desarrollo de los ferrocarriles en laArgentina antes de 1914’, Revista de Instituciones, Ideas y Mercados, 46, 2007. What suchaccounts overlook is the changes in the global political economy that made it possible for localactors to take such decisions.

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in foreign securities in Britain. British farming was struggling to compete with the

greatly increased supply of agricultural imports from the land-abundant countries,93

so the landed gentry, Britain’s traditional ruling class, diversified its assets out of

land, substantially fusing with the City of London’s financial sector. This gave birth

to a new ruling class of ‘gentlemanly investors’ who sought secure fixed-income

assets to provide a sufficient income to fund a gentleman’s lifestyle in government,

the arts, and the professions.94 Within Britain itself such assets were not available in

sufficient quantities, so the City of London increasingly looked abroad for invest-

ment opportunities, particularly to the land-abundant countries, where the long boom

was generating demand for investment in the infrastructure required to expand fronti-

ers, at the same time as buoyant exports provided the tax revenues that the govern-

ments of these countries needed to service foreign debts.95 During the second half of

the nineteenth century, the City of London thus came to specialise in exporting Brit-

ish capital overseas. Hence, foreign and colonial government bonds and railways

rose from eight percent of the value of the London Stock Exchange at mid-century to

59 percent in 1913.96 In total, there were listed £219 million of Argentine railway

securities, £129 million of Argentine government debt, and £76 million of securities

of companies that were predominantly operating in Argentina.97 Together, they made

up four percent of the nominal value of the London Stock Exchange, and roughly

two thirds of the stock of all foreign capital invested in Argentina.98

93. C.Ó. Gráda, ‘Agricultural Decline 1860-1914’, in R. Floud and D.N. McCloskey, eds., The Econ-omic History of Britain since 1700, II, 1860 to the 1970s, Cambridge, 1981; and M. Turner,‘Agriculture, 1860-1914’, in R. Floud and P. Johnson, eds., The Cambridge Economic History ofModern Britain, II, Economic Maturity, 1860-1939, Cambridge, 2004.

94. Cain and Hopkins, British Imperialism, chs. 2 and 3. The shift in sources of wealth is docu-mented in W.D. Rubinstein, Men of Property: The Very Wealthy in Britain since the IndustrialRevolution, 2nd ed., London, 2006, ch. 7.

95. Cain and Hopkins, British Imperialism, ch. 6; also R.C. Michie, The London Stock Exchange: AHistory, Oxford, 1999, ch. 3.

96. Based on the nominal value of all shares on the official list. Michie, London Stock Exchange, p.88, Table 3.2.

97. This is a corrected version of the widely used estimates of I. Stone, ‘The Composition and Distri-bution of British Investment in Latin America, 1865 to 1913’, PhD diss., Columbia University,1962, p. 153A, Table 43; also used in idem, ‘British Long-Term Investment in Latin America,1865-1913’, Business History Review, 42:3, 1968; and idem, ‘British Direct and Portfolio Invest-ment in Latin America Before 1914’, Journal of Economic History, 37:3, 1977. Stone’s calcula-tions (‘Composition and Distribution’, pp. 337, 406) show that he misunderstood the way inwhich Argentina’s currency system worked: for 1905 he used an exchange rate of $6.40 perpound to convert paper pesos, and in 1913 he used $5.04 per pound, whereas the correctexchange rate was $11.45 per pound, which has been applied to his figures here.

98. Calculated by dividing Stone’s adjusted figure of £424 million by an estimate of £645 million offoreign capital in Argentina in 1913, from V.L. Phelps, The International Economic Position of

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Figure 4.4Immigration and British Investment in Argentina, 1865-1913

-1

0

1

2

3

4

5

6

7

8

0

1

2

3

4

5

6

7

1865 1870 1875 1880 1885 1890 1895 1900 1905 1910 1915

British investment** £ per capita (right)

Net immigrants* per 100 people (left)

* Net immigration, calculated by subtracting departures from arrivals.

** New capital issues for Argentine government bonds and Argentina-based companiesissued on the London Stock Exchange.

Sources:

New capital issues: I. Stone, The Global Export of Capital from Great Britain, 1865-1914: AStatistical Survey, Basingstoke, 1999, pp. 62-71, Table 3.

Net immigration and population: Recchini de Lattes and Lattes, eds., Población de Argentina,pp. 199-200, Tablas 1 and 2.

Figure 4.4 illustrates how British investment came in three waves, with each

accompanied by a wave of immigrants, mainly from Southern Europe. The first wave

peaked in 1871, the second in 1888, and the third in 1909.99 They occurred as part of

Argentina, London, 1938, p. 246, Table 6. Not all of that capital was British because some wouldhave come from foreigners investing in London, but, on the other hand, much of the investmentcoming into Argentina from continental European stock markets would have been from Britishinvestors moving their capital abroad. See R. Michie, ‘Different in Name Only? The LondonStock Exchange and Foreign Bourses, c. 1850–1914’, Business History, 30:1, 1988. On thenumerous problems involved in the measurement of stocks of foreign capital in this period, seeD.C.M. Platt, Britain's Investment Overseas on the Eve of the First World War: The Use andAbuse of Numbers, Basingstoke, 1986; and C. Feinstein, ‘Britain's Overseas Investments in1913’, Economic History Review, 43:2, 1990.

99. These estimates of British capital exports are calculated from new issues on the British stockexchanges, with adjustments made for issues bought by foreigners. See M. Simon, ‘The Patternof New British Portfolio Foreign Investment, 1865-1914’, in I. Stone, The Global Export ofCapital from Great Britain, 1865-1914: A Statistical Survey, Basingstoke, 1999, pp. 421-30.

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Table 4.1British Capital Exports, 1865-1913

Argentina Australia Brazil Canada South Africa USAArgentina 1.00Australia 0.14 1.00Brazil 0.47 0.05 1.00Canada 0.42 0.06 0.63 1.00South Africa 0.02 0.01 0.00 0.01 1.00USA 0.50 0.05 0.38 0.56 0.06 1.00

Note: The matrix shows the coefficients of determination (R2s) between the British capitalexports to each country during 1865-1913. R2 measures the proportion of variation in oneseries that is determined by the variation in the other.

Source: Calculated from Stone, Global Export, pp. 42-81, 92-111, Tables 1-4, 6, and 7.

the transatlantic ‘Kuznets cycles’, which were named after Simon Kuznets, the econ-

omist who first observed them in the United States.100 Kuznets, and subsequently

many others, suggested that they were caused by the migration of Europeans to the

Americas, which increased the demand for infrastructure, so European capital

followed European labour across the Atlantic to finance it.101 Yet it seems more likely

that both were responding to the boom-bust cycles of westward expansion in the

United States, which were intimately linked to the terms of trade. When export

prices, especially wheat prices, rose, the frontier was pushed westward, attracting

European capital and labour due to greater enthusiasm for the prospects of settlement

in the new world.102 Argentina would ride on the coattails of the United States’

expanding frontier, as it benefited from the temporary mania in London for the secur-

ities of land-abundant countries. As illustrated by the coefficient-of-determination

(R2) matrix shown in Table 4.1, there were strong correlations between the flows to

Argentina, Brazil, Canada, and the United States, with all four Atlantic countries

experiencing similar movements in their inflows of British capital. Hence, in statist-

ical terms, half of the variation in the flow of British capital to Argentina was determ-

100. S. Kuznets, Capital in the American Economy: Its Formation and Financing, Princeton, 1961,ch. 7; also idem, ‘Long Swings in the Growth of Population and in Related Economic Variables’,Proceedings of the American Philosophical Society, 102:1, 1958.

101. Kuznets, Capital in the American Economy, pp. 327-41; also M. Abramovitz, ‘The Nature andSignificance of Kuznets Cycles’, Economic Development and Cultural Change, 9:3, 1961; R.A.Easterlin, ‘Economic–Demographic Interactions and Long Swings in Economic Growth’, Amer-ican Economic Review, 56:5, 1966; and B. Thomas, Migration and Economic Growth, rev. ed.,Cambridge, 1973.

102. North, Economic Growth, pp. 91, 94, 123-25, 136-40; Harley, ‘Transportation, the World WheatTrade’, pp. 233-37; cf. idem, ‘Western Settlement’.

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ined by flows to the United States.103 European immigrants then followed it across

the Atlantic because the demand for labour in Argentina increased as a result of the

construction of the new infrastructure and the new land that it brought into

production.104

The waves of British capital exports ebbed once it became apparent that fron-

tiers had been overextended in the land-abundant countries. With the new land being

brought into production, the supply of agricultural products to European markets

grew, so grain prices fell, resulting in a slower westward movement in the United

States. American railway companies then found that they had overextended the

network, reducing their profitability.105 The mania in London for foreign securities

then turned into a panic, typically leading to financial crises in the land-abundant

countries when capital inflows dried up. In Argentina these crises began because

government finances remained heavily dependent upon the customshouse, which

fluctuated with the ebbs and flows of British capital. When capital was flowing in,

imports increased, leading to greater revenues, which allowed more expenditure.

When the wave ebbed, however, austerity had to be imposed, which brought a reces-

sion that reduced demand for labour, so the flow of immigrants dried up. In both the

early 1870s and the early ‘90s these recessions were accompanied by major unrest,

as the rhythms of Argentina’s political economy came to be determined by the cycles

of a globalising capitalism centred on the North Atlantic.106

103. Davis and Gallman claim that there was little correlation in the timing of the flows of Britishcapital to the various land-abundant countries based on the R2s between annual series of the newissues on the London Stock Exchange for Argentina, Australia, Canada, and United States during1865-1914; they conclude that ‘there is little evidence of any significant degree of associationbetween them’. Davis and Gallman, Emerging Financial Markets, p. 34. Their findings are atodds, however, with the better-document Simon-Stone estimates of British capital exports. Ascan be seen in Table 4.1, replicating Davis and Gallman’s methodology (from Emerging Finan-cial Markets, p. 35, Table 1:4-8) with the Simon-Stone data shows that 50 percent of the varia-tions in Argentina’s flows were determined by variations in the flows to the United States, yet, intheir equivalent R2 matrix, Davis and Gallman claim that it was just 0.1 percent! Explaining thisdifference is difficult because Davis and Gallman did not reproduce their annual series for theUnited States, which is where the problem must lie, given that their series for Argentina (Emer-ging Financial Markets, pp. 706-07, Table 6:4-6(a)) is very similar to the Simon-Stone estimates.The only major difference is for 1903, when Davis and Gallman claim there were an astonishing£55 million of new calls for Argentine railway companies, compared to just £3.7 million in theSimon-Stone series (Stone, Global Export, p. 69, Table 3).

104. This direction of causality from capital flows to labour flows is demonstrated for the case ofItalian emigration in S. Fenoalta, ‘International Resource Flows and Construction Movements inthe Atlantic Economy: The Kuznets Cycle in Italy, 1861-1913’, Journal of Economic History,48:3, 1988.

105. Harley, ‘Transportation, the World Wheat Trade’, pp. 235, 237.106. Belich provides a useful overview of these boom-bust cycles, although he does not see their

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The first, least substantial wave of British investment occurred during

1865-77, mainly under the presidencies of Bartolemé Mitre (1862-68) and Domingo

Sarmiento (1868-74), two liberal intellectuals who had been exiled under Rosas.107

Following the downfall of Rosas, they had returned with the goal of resurrecting

Rivadavia’s project of unifying Argentina under a strong central government based in

Buenos Aires – a project that was finally becoming feasible due to the outward turn

in Britain’s gentlemanly capitalism. Buenos Aires had always enjoyed a financial

superiority vis-à-vis the other provinces thanks to its customshouse revenues. Yet it

was only once those revenues were capitalised – that is, when future customshouse

revenues were discounted into present values – that it became possible to construct

the kind of infrastructure that a government based in Buenos Aires required to prop-

erly control its territory, thus facilitating state building based on ‘capitalised coer-

cion’.108 In 1862 a concession was given to a North American businessman in which

the government guaranteed a fixed rate of return on the railway that he was to

construct and operate.109 Anglo-Argentine merchants and financiers were then able to

use the promise of such concessions to promote Argentine railways among British

investors, also taking the opportunity to invest their own capital in Argentine

companies floated in London.110 Moreover, the public railways began to expand after

1863, when the government promised that all its foreign loans would be repaid in

London in sterling, thereby reassuring British investors that the country’s debts

would be serviced.111 With this institutional framework in place, the first wave of

British investment began. During 1865-77, 25 percent went into railway companies,

and 60 percent was placed in government bonds, although much of that was in turn

invested in the public railway companies.112 The network consequently expanded

from just 47 km in 1865 to 2,200 km in 1877, while 204,000 immigrants settled,

mainly in the Littoral region.113 The railways then not only gave the national army a

connection to the terms of trade, believing them instead to be the result of collective hysteria.Belich, Replenishing the Earth, pp. 85-89.

107. On these philosopher-statesmen, see Shumway, Invention of Argentina, chs. 7-8.108. Cf. C. Tilly, Coercion, Capital, and European States, AD 990-1992, Oxford, 1992.109. Lewis, British Railways, pp. 10-13; and Regalsky, ‘Políticas públicas’, pp. 178-79.110. Ferns, Britain and Argentina, pp. 329-38; Reber, British Mercantile Houses, ch. 6; Lewis, British

Railways, pp. 18-22; and idem, ‘Anglo-Criollo’, pp. 256-59.111. Ferns, Britain and Argentina, p. 326.112. Palermo, ‘Nation Building Mission’, pp. 68-70.113. Here and in the subsequent paragraph, numbers on British investment are calculated from Stone,

Global Export, pp. 62-71, Table 3; numbers on net immigration are from I. Ferenczi and W.F.

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far greater mobility, but a greater labour supply also made it easier to conscript

soldiers.114 A new transportation system, together with an expanding population, in

this way increased the federal government’s capacity to put down the revolts against

it that occurred during the 1860s and ‘70s,115 so it was able to secure the position of

its supporters among the provincial ruling classes, insulating them against the discon-

tent of their peasantries.116

During the second and third waves of British investment, the provincial

ruling classes would themselves take the lead. After the peak of the first wave in

1871, there followed a major financial crisis in 1873, which substantially undermined

support for the Buenos Aires liberals. As a result, in the 1874 elections a coalition of

provincial governors was able to engineer the victory of their candidate, Nicolás

Avellaneda of the National Autonomist Party (PAN). Mitre immediately rebelled, but

his uprising was put down, as was another rebellion in Buenos Aires in 1880, which

finally led to the city’s juridical separation from its province and establishment as the

Federal Capital. The PAN would then exercise a long hegemony over Argentine

politics, with its power base largely in the interior, where the governors used wide-

spread electoral fraud to maintain its rule.117

During the administrations of Avellaneda (1874-80), Julio Roca (1880-86),

and Miguel Ángel Juarez Celman (1886-90) the PAN channelled further British

investment into the interior’s railway network. This required more public subsidies to

encourage investors to build what would be less heavily trafficked lines, so the profit

guarantees for private railway companies were continued, with foreign loans also

Willcox, International Migrations, I, Statistics, New York, 1929, pp. 453-46, Table 5; andRecchini de Lattes and Lattes, eds., Población de Argentina, pp. 199-200, Tablas 1 and 2; andnumbers on the railway network are from Tornquist, Economic Development, pp. 116-17.

114. Resistance to conscription had long been a problem in the Littoral. Salvatore, ‘Reclutamientomilitar’, pp. 38-41; and idem, Wandering Paysanos, pp. 264-67. It was also resented by landown-ers due to its effects on the labour supply. Halperín Donghi, ‘Buenos Aires Landed Class’, pp.52-53.

115. Rock, State Building, ch. 2.116. Again, this had long been a problem in the interior that had prevented the formation of a unified

state. See de la Fuente, Caudillo and Gaucho; also Paz, ‘Province and Nation’. Under the 1853constitution, after the railway network was established, federal interventions in the provinceswould become common. N.R. Botana, El orden conservador: La política argentina entre 1880 y1916, 2nd ed., Buenos Aires, 1985, pp. 121-37.

117. On the PAN’s rule, see Botana, Orden conservador, chs. 3-6; Alonso, Between Revolution, ch. 1;and Rock, State Building, chs. 3-5. Politics was somewhat more competitive in Buenos Aires,although elections were still far from being free and fair. H. Sabato, The Many and the Few:Political Participation in Republican Buenos Aires, Stanford, 2001.

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used to establish more state-owned railways.118 By the early 1890s, almost three

quarters of the length of the interior’s railways were either state owned or being

subsidised by a profit guarantee, whereas most of the Littoral’s line were being oper-

ated without such subsidies.119 In total, during the 1878-93 wave 47 percent of British

investment went directly into railway companies, and 36 percent went to the govern-

ment, which spent much of it on profit guarantees and on financing its own railway

companies. Consequently, the network expanded from 2,200 km in 1877 to 13,900

km in 1893, while 739,000 immigrants settled. Again, however, the peak of the wave

in 1888 was followed by a major financial crisis when the government found that it

was unable to service its foreign debts without fresh inflows of foreign capital. The

result would become known as the Barings Crisis after the government defaulted in

1891, leaving its principal underwriter, Barings Bank, with millions of pounds of

Argentine stock that it had underwritten but could not sell, which almost bankrupted

it.120 Austerity then provoked a recession that made immigration dry up and triggered

an armed rebellion by the Radical Civil Union (UCR), a newly formed political party

mainly based in Buenos Aires.121 Prosperity was nevertheless restored by the third

wave. During 1894-1913 the railways expanded to 32,500 km, and 2.1 million

immigrants settled. This time, 67 percent of British investment went into railway

companies, with just 11 percent going into government debt, as the PAN avoided a

repeat of massive government borrowing. Instead, it consolidated its finances by

abolishing the profit guarantees, placing constraints on the provinces’ capacity to

borrow, restructuring the public debt, and increasing its revenue base by imposing a

series of taxes on domestic production, thereby reducing its historical dependence on

the customshouse and insulating it somewhat from future financial crises.122

118. Palermo, ‘Nation Building Mission’, pp. 70-71; and Llach, ‘Wealth of the Provinces’, pp. 70-90.119. Calculated from DFN, Estadística de los Ferrocarriles en Explotación, 1892, pp. 64-6, Table 2.

According to these figures, in 1892 just 16 percent of the lines (in terms of length) in the Littoralwere being operated with a profit guarantee, compared to 54 percent in the interior, with another38 percent of the interior’s lines owned by the government, with no public lines operated in theLittoral. That said, it should be remembered that all lines were operating with some kind ofgovernment support, particularly tax breaks in the form of low or non-existent import tariffs, aswell as land grants. See A.M. Regalsky, Las inversiones extranjeras en la Argentina (1860-1914),Buenos Aires, 1986, pp. 34-35; and idem, ‘Políticas públicas’, pp. 183-84.

120. A.G. Ford, ‘Argentina and the Baring Crisis of 1890’, Oxford Economic Papers, 8:2, 1956;Ferns, Britain and Argentina, ch. 14; idem, ‘The Baring Crisis Revisited’, Journal of Latin Amer-ican Studies, 24:2, 1992; and Duncan, ‘Política fiscal’.

121. Alonso, Between Revolution, chs. 2-3.122. D.J. Guy, ‘Carlos Pellegrini and the Politics of Early Argentine Industrialization, 1873–1906’,

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Much as Alberdi had predicted, these waves of British investment unified the

country territorially, which then brought political unity. The greater mobility given to

the national army by the railways allowed the federal government to bolster the posi-

tion of those who supported it in the provinces. Furthermore, the railways also

provided opportunities for provincial ruling classes to profit from the terms-of-trade

boom.123 For the first time, ruling-class groups across the country stood to gain from

the long boom: landowners in Córdoba could bring their land into production for

export thanks to the reduced costs of internal transportation; leading families in the

North and West could, for the same reason, invest in industries to supply the Litt-

oral’s expanding market;124 the Littoral’s merchants could become financiers working

with foreign investors or could invest in industries to supply the newly enlarged

national market;125 and Buenos Aires’ landowners benefited from the expansion of

the frontier, especially after the railways had facilitated the final defeat of the

Pampean Indians.126 As different interests were reconciled, ruling-class families

across the country started to fuse, resulting in the emergence of a national ruling

class.

Roca, twice president during 1880-86 and 1898-1904, embodied what

became known as the ‘oligarchy’. Having begun as an army officer from a prominent

family in Tucumán, he had married into a prominent family from Córdoba, then

came to national prominence by leading the Conquest of the Desert against the

Pampean Indians in 1879-80.127 Once president, the provincial government of

Buenos Aires, also controlled by the PAN, made a generous donation of land that,

together with the donations received by his two brothers in the newly conquered La

Pampa territory, turned the Rocas into one of the Pampas’ most significant landown-

ing families.128 Such use of public offices to accumulate Pampean land would

Journal of Latin American Studies, 11:1, 1979, pp. 131-40.123. Cf. Ansaldi, ‘Notas sobre la formación’, pp. 550-52. 124. Balán, ‘Cuestión regional’; D.J. Guy, Argentine Sugar Politics: Tucumán and the Generation of

Eighty, Tempe, 1980, ch. 2; and Losada, Historia de la elites, pp. 146-52.125. Reber, British Mercantile Houses, ch. 6; C.M. Lewis, ‘‘Anglo-Criollo’ Rather than British: Early

Investments in Argentinian Railways and Utilities’, in Schvarzer, Regalsky, and Gómez, eds.,Estudios sobre la Historia, pp. 223-70; Rocchi, Chimneys in the Desert, ch. 4; and Pineda, Indus-trial Development, ch. 4.

126. C.M. Lewis, ‘La consolidación de la frontera argentina a fines de la década del 70: Los indios,Roca y los ferrocarriles’, in G. Ferrari and E. Gallo, eds., La Argentina del ochenta al centenario,Buenos Aires, 1980; and R. Hora, The Landowners of the Argentine Pampas: A Social and Polit-ical History 1860-1945, Oxford, 2001, pp. 41-44.

127. Rock, State Building, pp. 93-95, 100-01, 104-05.

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become widespread among the PAN’s leaders, many of whom turned themselves into

major landowners.129 Meanwhile, members of the Pampean landowning class moved

in the opposite direction by integrating with the leading families of the interior

through marriage,130 and associations, particularly the Jockey Club in Buenos Aires,

provided an environment where even those who were not family could bond.131 A

national ruling class would thus form at the summit of an oligarchic state, linked by

family and social networks that mirrored those of the new transportation system.

British investment was, then, the key to the emergence of Castlereagh’s

native force. Big business became dominated by foreigners, especially the British, at

the same time as Argentina’s national ruling class – its ‘internal bourgeoisie’132 –

specialised in landownership. Of Argentina’s top 100 corporations, according to a

survey included in the 1914 census, only 22 were purely Argentine, with the first and

third largest Argentine companies both public banks. Another 44 corporations were

mixed Argentine-foreign, with the remaining 34 completely foreign. The 24 British

corporations made up fully 46 percent of the capital issued by all 100.133 Domestic

investors, by contrast, made up the bulk of the landowning class. Hence, the 1908

agricultural census found that just four percent of the value of the country’s rural

establishments consisted of properties owned by foreign residents.134 Land had

instead become the primary asset of Argentina’s own ruling class. In the interior the

railway network allowed provincial ruling classes to use their land to supply the Litt-

oral’s market,135 while in the Littoral itself those families that had diversified into

128. Hora, Landowners of the Argentine Pampas, pp. 37, 62.129. Sesto, ‘Implementación de la política’, esp. pp. 410-11; and Rock, State Building, p. 105-06.130. Balmori, Voss, and Wortman, Notable Family Networks, p. 134; and O. Favaro and M.B.

Morinelli, ‘El Noroeste y su vinculación con el estado nacional: Repensando la alianza del 80’, inW. Ansaldi, A. Pucciarelli, and J.C. Villarruel, eds., Argentina en la paz de dos guerras1914-1945, Buenos Aires, 1993, p. 138.

131. T.M. Edsall, ‘Elites, Oligarchs, and Aristocrats: The Jockey Club of Buenos Aires and the Argen-tine Upper Class, 1920-1940’, PhD diss., Tulane University, 1999, ch. 1; and L. Losada, ‘Sociab-ilidad, distinción y alta sociedad en Buenos Aires: Los clubes sociales de la elite porteña’, Desar-rollo Económico, 45:180, 2006, pp. 547-72.

132. On the concept of the internal bourgeoisie, see N. Poulantzas, Classes in Contemporary Capital-ism, London, 1975, pp. 72-73. It is somewhere between the ideal types of a ‘comprador bour-geoisie’ (that is, entirely subservient to foreign capital) and a ‘national bourgeoisie’ (that is,wholeheartedly committed to national development).

133. Nationality was established based on where the share and bonds were emitted and/or held. Calcu-lated from CNC, Tercer censo nacional, X, Valores mobiliarios y estadísticas diversas, BuenosAires, 1917, pp. 2-81. For the list of the 100 corporations, see Table DA.18 in the Data Appendix.

134. Calculated from República Argentina, Censo agropecuario nacional: La agricultura y laganadería en 1908, II, Agricultura, Buenos Aires, 1909, pp. 438-49.

135. Balán, ‘Cuestión regional’.

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landownership in the first half of the century, such as the Anchorenas,136 increasingly

specialised in it during the second half, becoming conscious of themselves as a

landowning class.137 Their probate inventories demonstrate the extend to which their

assets were dominated by land.138

Having disordered the River Plate during the first half of the nineteenth

century, the long boom had thus created a new order in Argentina based on an olig-

archic state dominated by a landowning ruling class. This had been made possible

because, responding to the crisis in British agriculture provoked by the greater supply

of imported food, Britain’s gentlemanly investors had sought alternative assets. They

found them in land-abundant countries such as Argentina, which required substantial

investment in infrastructure to expand its frontiers and, more importantly, had the

means to service foreign investments due to the growing export sector. In Argentina

the result of the outward turn in Britain’s gentlemanly capitalism was the construc-

tion of a railway network that greatly augmented the capacity of the federal govern-

ment to control its territory, thereby enabling it to reinforce the position of its

supporters in the provinces. What is more, territorial unity would then encourage

business, family, and social links between the country’s different ruling classes, lead-

ing to the formation of a national ruling class that increasingly specialised in

landownership, even as Britain’s old landed gentry diversified into finance.139

The Emerging NationOptimistic historians have enthusiastically celebrated Argentina’s progress under the

oligarchic state.140 Progress was seen most clearly in the growth of territory, popula-

136. Hora, Landowners of the Argentine Pampas, pp. 82-83; and idem, ‘Anchorena: Patrones’, pp.50-51.

137. Hora, Landowners of the Argentine Pampas, chs. 1-2.138. R. Hora, ‘Landowning Bourgeoisie or Business Bourgeoisie? On the Peculiarities of the Argen-

tine Economic Elite, 1880-1945’, Journal of Latin American Studies, 34:3, 2002; and idem, ‘Elperfil económico’. Hora’s research has refuted Sábato’s hypothesis that Argentina’s ruling classhad highly diversified assets. J.F. Sábato, La clase dominante en la Argentina moderna: Forma-ción y características, 2nd ed., Buenos Aires, 1991. Where both agree is that it was a capitalistclass, as opposed to some remnant of feudalism. On the debate surrounding Sábato’s hypothesis,see M.I. Barbero, ‘La historia de empresas en la Argentina: Trayectoria y temas en debate en lasúltimas dos décadas’, in Gelman, ed., Historia económica argentina, pp. 158-61.

139. For illustrations of how this opposite movement also occurred on a cultural level, see R. Hora,‘Britain, the British Landed Class, and Argentine Landowners’, Canadian Journal of Latin Amer-ican and Caribbean Studies, 30:59, 2005.

140. See, above all, Cortés Conde, Progreso argentino; idem, ‘Export Economy’; idem, ‘Growth ofthe Argentine Economy’; idem, Economía argentina; and idem, ‘Vicissitudes of an Exporting

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tion, and trade. By facilitating the final defeat of the Indians, the railways allowed the

federal government to enlarge the territory under its control from around 1.9 million

square kilometres at the end of the 1860s to 2.8 million by the eve of the First World

War.141 Reduced internal transportation costs then permitted more land to be brought

into production: the hectares under cultivation increased from around 600,000 at the

beginning of the 1870s to 24 million in 1913.142 This arable expansion brought

rapidly growing exports of cereals and oilseeds, which drove an annual growth rate

of around five percent in the volume of exports.143 Immigrants provided much of the

labour for this expansion, with around three million foreigners, mainly Italians and

Spanish, settling from the 1860s through to the First World War, leading to a popula-

tion growth of 3.3 percent per year144 – faster than any of the other major land-abund-

ant countries.145 These were the most important signs of progress in Argentina during

the late nineteenth century.146

Through this extensive growth a new society came into being centred on the

Littoral. Having accounted for roughly a third of the country’s population in 1809,147

the Littoral’s share rose to 46 percent by 1869, then further to 68 percent in 1914, as

seen in Table 4.2. From 1869 to 1895 this was because of the faster expansion of the

Littoral as a whole, but from 1895 to 1914 it was purely due to the rising share of

Buenos Aires. Immigrants flocked to the city: in 1914 fully 68 percent of the Federal

Capital’s adult population was foreign, compared to 48 percent in the rest of the Litt-

oral, and just 28 percent in the interior.148 The foreigners were mainly Southern

Europeans who had been attracted to Argentina by higher wages and cheaper land.

Economy’.141. Estimated from Superintendente del Censo, Primer censo, p. 672; and CNC, Tercer censo

nacional, III, Población, Buenos Aires, 1916, p. 58. It was assumed that the indigenous-occupied‘national territories’ were not under the federal government’s control when the 1869 census wastaken. For the role of the railways, see Lewis, ‘Consolidación de la frontera’.

142. Tornquist, Economic Development, p. 26.143. H. Diéguez, ‘Crecimiento e inestablidad del valor y el volumen físico de las exportaciones argen-

tinas en el periodo, 1864-1963’, Desarrollo Económico, 12:46, 1972, p. 349, Cuadro 18.144. Recchini de Lattes and Lattes, eds., Población de Argentina, pp. 199-200.145. Australia grew at a trend rate of 2.4 percent per year; Canada at 1.5 percent; the United States at

2.1 percent. Calculated from Maddison, World Economy, II, pp. 459-60, Table 2a.146. Optimists also point toward dramatic GDP per capita growth. They make these observations,

however, on the basis of Mickey Mouse numbers, as was discussed in Appendix 1.1, especiallypages 45-53.

147. Comadrán Ruiz, Evolución demográfica argentina, p. 115.148. In the Centre they were 28 percent; in the North, 21 percent; in the West, 30 percent; in the newly

colonised South, 63 percent. Calculated for the population aged 18 and over from CNC, Tercercenso, III, pp. 18-294.

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Table 4.2Argentina’s Population, 1869-1914

TotalGreaterBuenosAires*

OtherLittoral

TotalLittoral Centre West North South

(a) 1,000s of people1869 1,830 225 623 848 418 254 287 241895 3,955 767 1,747 2,514 620 375 432 151914 7,885 1,999 3,316 5,315 1,215 606 672 78

(b) % of total population1869 100.0 12.3 34.0 46.3 22.8 13.9 15.7 1.31895 100.0 19.4 44.2 63.6 15.7 9.5 10.9 0.41914 100.0 25.4 42.1 67.5 15.4 7.7 8.5 1.0

* Metropolitan area, including the Federal Capital and the surrounding urban counties ofBuenos Aires Province.

Note: The composition of the regions is as follows:

Littoral: Buenos Aires, Corrientes, Entre Rios, Federal Capital, and Santa Fe.

Centre: Córdoba, La Pampa, San Luís, and Santiago.

West: Catamarca, La Rioja, Mendoza, Neuquén, and San Juan.

North: Chaco, Formosa, Jujuy, Los Andes, Misiones, Salta, and Tucumán.

South: Chubut, Rio Negro, Santa Cruz, and Tierra del Fuego.

Sources: Comisión Directiva, Segundo censo de la República Argentina, II, Población,Buenos Aires, 1898, p. cxlix, Cuadro 1; CNC, Tercer censo nacional, I, Población, BuenosAires, 1916, p. 65; and G. Germani, Estructura social de la argentina: Análisis estadístico,Buenos Aires, 1955, p. 74, Cuadro 26.

Many became tenant farmers in the Pampean zone, then moved to the city with their

savings to establish themselves when their contracts ended. Others used their connec-

tions in Europe to access lines of credit that could be invested in trade and industry,

which allowed them to take advantage of linkages with the export sector. Immigrants

also tended to be better trained than the native born, so they provided much of the

manpower for the Littoral’s growing industrial sector. Often they could enjoy rapid

social mobility, forming the bulk of the country’s middle classes.149 They, together

149. J.R. Scobie, Revolution on the Pampas: A Social History of Argentine Wheat, 1860-1910, Austin,1964, ch. 3; Germani, Política y sociedad, pp. 253-67; H.S. Klein, ‘The Integration of ItalianImmigrants into the United States and Argentina: A Comparative Analysis’, American HistoricalReview, 88:2, 1983, pp. 313-15, 319-23; D.J. Guy, ‘Dependency, the Credit Market, and Argen-tine Industrialization, 1860-1940’, Business History Review, 58:4, 1984, p. 540; Adelman, Fron-tier Development, pp. 108-16; J.C. Moya, Cousins and Strangers: Spanish Immigrants in BuenosAires, 1850-1930, Berkeley, 1998, ch. 5; and S.L. Baily, Immigrants in the Lands of Promise:Italians in Buenos Aires and New York City, 1870-1914, Ithaca, 1999, pp. 100-01, 113-15,118-19.

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with the landowning class, were the main beneficiaries of Argentina’s extensive

growth.

Yet the new society centred on Buenos Aires was not representative of Argen-

tina as a whole: outside the capital city much of the emerging nation consisted of a

floating population of unskilled, landless labourers who depended upon unsteady

forms of employment to survive. Their principal period of employment came during

the harvest, when around 600,000 extra people were needed every year by the eve of

the First World War.150 Once the harvest was over, they dispersed, with some going to

the cities to find work, and others farming small plots of marginal land that they

either owned or were squatting.151 In the census data on occupations, compiled in

Table 4.3, the growth of this floating population can be seen: the 1869 census found

that day labourers (also described as ‘hard up people without fixed work’) made up

19 percent of the labour force, which then increased to 21 percent in the 1895 census,

and to 26 percent in the 1914 census, which recorded 807,297 men and 21,982

women who were described as ‘jornaleros’ and ‘peones’;152 half were Argentines,

half were foreigners. Hence, the floating population had been formed by the conflu-

ence of Argentina’s landless labourers with those of Southern Europe.

153

The floating population grew so rapidly because access to the land was

restricted by the concentration of landownership. While there were some successful

attempts to establish ‘colonies’ of smallholding arable farmers,154 most of the

publicly-owned lands continued to be privatised in a way that favoured the concen-

150. The estimates vary considerably. See M.A. Ballesteros, ‘Argentine Agriculture, 1908-1954: AStudy in Growth and Decline’, PhD diss., University of Chicago, 1958, pp. 75-81.

151. Traditionally it was assumed that most of the harvest workers were so-called ‘swallows’ (golon-drinas) – that is, Southern Europeans who would come each year to work on the harvest in theSouthern Hemisphere, before returning for the harvest in their own country. However, thisphenomenon must have been massively overstated simply because the amount that could beearned in a single harvest was insufficient to cover the return fare back to Europe. Rather, mostwere long-term residents – whether native born or immigrant. See Adelman, Frontier Develop-ment, pp. 118-22.

152. The previous censuses did not separate them in this way, so it is necessary to group them here tomake the 1914 census comparable. In 1914, 85 percent were jornaleros, 13 percent peones, andtwo percent peones de campo.

153. For the Pampean zone, see Solberg, ‘Farm Workers’; also Adelman, ‘Harvest Hand’; idem, Fron-tier Development, pp. 116-30. For the North and West, see Balán, ‘Migraciones, mano de obra’;Guy, ‘Rural Working Class’; and Salvatore, ‘Labor Control’.

154. The classic study is E. Gallo, La pampa gringa: La colonización agrícola de Santa Fe,1870-1879, Buenos Aires, 1983; see F. Rocchi, ‘Una pasión inquebrantable por la historia:Ezequiel Gallo y la historiografía argentina’, Revista de Instituciones, Ideas y Mercados, 46,2007, pp. 22-25.

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Table 4.3Argentina’s Day Labourers, 1869-1914

Total FederalCapital

OtherLittoral Centre West North South

(a) Number of workers1869 163,989 10,200 84,413 33,176 19,513 16,687 ...1895 342,493 28,463 196,217 45,285 27,084 44,046 1,3981914 829,269 82,659 476,761 121,810 52,135 82,210 13,694

(b) % of total occupations1869 19.1 10.3 29.1 15.2 15.7 13.2 ...1895 20.8 9.3 27.1 17.8 16.3 23.2 21.91914 25.6 10.4 34.0 25.2 23.3 27.5 40.1

* Includes the following categories:

1869: jornaleros, peones, gañanes, etc.

1895: jornaleros.

1914: jornaleros; peones de campo; peones.

Note: For the composition of the regions, see Table 4.2.

Sources: Calculated from Superintendente del Censo, Primer censo, pp. 642-669; ComisiónDirectiva, Segundo censo, II, pp. 47-50, 139-142, 183-186, 216-219, 257-60, 297-300,326-29, 365-68, 402-05, 439-42, 476-79, 515-16, 552-55, 592-95, 624-27, 706-09; and CNC,Tercer censo, IV, Población, Buenos Aires, 1916, pp. 201-329.

tration of landownership. Land conquered during the Conquest of the Desert in

1879-80 was mainly distributed in vast lots to capitalists who had taken up the bonds

that financed the military campaign against the Indians.155 Some 11 million hectares

of Pampean land were distributed to 344 landowners, which was equivalent to over

31,000 hectares each.156 By the mid-1880s there was no more publicly-owned

Pampean land to distribute.157 Thereafter, what is more, laws ostensibly designed to

redistribute the land were often abused. Most notoriously, Buenos Aires Province’s

Arable Centres Law of 1887 was supposed to encourage great landowners to sell

small lots to arable farmers, yet national and provincial deputies and senators, magis-

trates, and other members of the PAN instead used it to accumulate land themselves

with public funds.158 Furthermore, the banking system established under the PAN

155. R. Gaignard, La Pampa Argentina: Ocupación, poblamiento, explotación: De la conquista a lacrisis mundial (1550-1930), Buenos Aires, 1989, pp. 227-66; also Cárcano, Evolución histórica,ch. 14.

156. Gaignard, Pampa argentina, p. 261.157. Ibid., p. 253.158. Sesto, ‘Implementación de la política’, esp. pp. 410-11.

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also encouraged concentration by making landownership the principle means of

obtaining credit from the large public banks; landowners then used that credit to

increase their holdings,159 which further concentrated ownership. Argentina attracted

more unskilled Southern European labourers, as a result, given that they were willing

to farm the land as tenants. Even they, nevertheless, found it more difficult to rent

land as their numbers grew, so instead they swelled the ranks of the floating

population.160

Landownership even became more concentrated in long-settled regions,

despite the breakup of the greatest estates due to their division among heirs. Optim-

istic historians have often misunderstood this process because they have confused a

reduction in the number of massive holdings and a proliferation of smaller ones with

less concentration.161 Hilda Sabato, however, found that ‘although the number of

large holdings and the total amount of land under the control of the latifundistas may

have diminished significantly, inequalities were enlarged, and fewer men had owner-

ship of relatively more land’.162 Figure 4.5 reproduces her evidence, which comes

from a study of holdings of over 100 hectares in the property-registry maps of 16

counties in northern Buenos Aires Province in 1836, 1864, and 1890.163 The Lorenz

curves show rising inequality over time, as they move further away from the diag-

onal line of perfect equality. The top 10 percent of holdings increased their share of

the land from 41 percent in 1836 to 49 percent in 1864, and to 55 percent in 1890,

with the Gini coefficients derived from these curves climbing from 0.52 in 1836 to

0.61 in 1864, and to 0.66 in 1890.164 Despite the claims of more optimistic historians,

159. Ferns, Britain and Argentina, pp. 370-76, 423-24; cf. Sábato, Clase dominante, pp. 105-08; andSabato, Agrarian Captialism, pp. 267-71; also Adelman, Frontier Development, pp. 86-88.

160. Adelman, Frontier Development, pp. 113-16, 131-32, 144-45, 158-59; also Scobie, Revolution onthe Pampas, ch. 3. On the growing share of Southern European unskilled labourers amongArgentina’s immigrants, see G. Beyhaut, R. Cortés Conde, H. Gorostegui, and S. Torado, ‘Losinmigrantes en el sistema ocupacional argentino’, in T.S. di Tella, G. German, J. Graciarena, et al,Argentina, sociedad de masas, 2nd ed., Buenos Aires, 1965, pp. 94-99.

161. Cortés Conde, Progreso argentino, pp. 107-17; and Taylor, ‘Latifundia as Malefactor’, pp.274-78.

162. Sabato, Agrarian Capitalism, p. 58.163. The results were reported in ibid., ch. 2; with the data in H. Sabato, ‘Wool Production and

Agrarian Structure in the Province of Buenos Aires, North of the Salado, 1840’s-1880’s’, PhDdiss., University of London, 1980, pp. 335, 340-41, Tables 3, 8 and 9; they are also reproduced inTable DA.19 in the Data Appendix.

164. These are for family holdings. Sabato’s data on individual holdings, also reproduced in TableDA.19, have a Gini coefficient of 0.49 in 1836, 0.55 in 1864, and 0.58 in 1890. To calculate theGini coefficients, Julien R. Barlan’s calculator was used. It is available online at http://www.juli-enbarlan.com/ (accessed 7 October 2013).

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Figure 4.5Land Distribution in 16 Counties of Buenos Aires Province, 1836-90

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

1836

1864 1890

% of land

Note: The Lorenz curves are for family landholdings of 100 hectares and over in the 16counties. The vertical axis shows the cumulative percentage of land held by the cumulativepercentage of family holdings, ranked by size, shown on the horizontal axis. The diagonalline is the line of perfect equality. The further a year’s line is from that line, the more unequalthe distribution of land among the families in that year.

Source: Sabato, ‘Wool Production’, pp. 335, 340-41, Tables 3, 8 and 9. Sabato’s data arereproduced in Tables DA.19 and DA.20.

therefore, land ownership became more concentrated under the PAN, as should be

expected from their land and credit policies.

In much of the interior the lack of access to the land was even more acute. In

the North and West there was relatively little land to distribute in the first place.

Figure 4.6 illustrates how cultivated land per capita did not increase substantially in

either region from the 1870s to the First World War. By 1913 there was just one

hectare of cultivated land per capita in the West, and even less in the North, whereas

in the Centre there were seven hectares per capita, and in the Littoral, despite the

rapid growth of Buenos Aires City, there were still three hectares per capita. Much of

the interior lacked, then, the vast, scarcely populated expanses of the Pampean

zone.165 Magnifying that, access to the land was more inequitably distributed where it

165. The South, on the other hand, was largely scrubland, and very scarcely populated.

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Figure 4.6Cultivated Land Per Capita in Argentina, 1872-1913

0

1

2

3

4

5

6

7

1870 1880 1890 1900 1910 1920

ha per capita Centre

Littoral

South

West

North

Note: The dots are for 1872, 1888, 1895, and 1913; the lines are interpolations between thosepoints. The populations of the regions were estimated by interpolating between nationalcensus data for 1869, 1895, and 1914. For the composition of the regions, see Table 4.2.

Source: Cultivated land: DGEE, Estadística Agrícola: Año Agrícola 1913-14, p. 15.Population: Comisión Directiva, Segundo censo, II, p. cxlix, Cuadro 1; and CNC, Tercercenso, I, p. 65.

was scarcest. The Lorenz curves in Figure 4.7 are calculated from data on agricul-

tural establishments recorded in the 1914 census. They illustrate how access to the

land was most concentrated in the North and West, as the curves for these regions are

considerably further from the line of perfect equality, which indicates a more unequal

access to land. Hence, the Gini coefficients derived from the curves are 0.88 for the

North and 0.93 for the West, compared to 0.77 for the Littoral, 0.78 for the Centre,

and 0.72 for the South.166 This more unequal access to the land in the North and West

was a reflection of how the interior’s ruling classes had used their control of provin-

cial legislatures to appropriate the best land.167

166. A similar pattern is seen for the size distribution of arable establishments: 0.77 for the North and0.82 for the West, compared to 0.56 for the Littoral, 0.57 for the Centre, and 0.53 for the South.Calculated from CNC, Tercer censo nacional, V, Explotaciones agropecuarias, Buenos Aires,1919, pp. 691-94. Again, Barlan’s calculator was used.

167. For examples, see Rock, State Building, pp. 65-66, 108-09, 159.

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Figure 4.7Land Distribution in Argentina, 1914

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

South

Littoral Centre

West North

% of land

Note: The vertical axis shows the cumulative percentage of land held by the cumulativepercentage of establishments, ranked by size, shown on the horizontal axis. The diagonal lineis the line of perfect equality. The further the regions’ lines are from that line, the moreunequal the distribution of land among the establishments. For the composition of the regions,see Table 4.2.

Source: Calculated from CNC, Tercer censo nacional, V, Explotaciones Agropecuarias,Buenos Aires, 1919, pp. 3-6.

Opportunities for internal migration to more land-abundant regions were also

limited for the interior’s predominantly native-born, mixed-race population due to

ethnic discrimination in the Pampean zone. In Santa Fe, a Littoral province that

famously succeeded in establishing smallholding family farms,168 the early land laws

stipulated that only European immigrants were allowed to become ‘colonists’, and

that they were not to sell their holdings to the native born.169 Similarly, in land-

abundant Córdoba, in the centre of the country, the 1871 colonisation law allocated

540,000 hectares of public land for settlement by immigrants, but made nothing

available for Argentines.170 More importantly, large landowners also preferred to rent

168. Gallo, Pampa gringa, ch. 7.169. Here the term ‘native born’ is not to be confused with the indigenous, as it also included creoles –

that is, those born in Argentina of (at least some) European ancestry.170. Solberg, ‘Farm workers’, p. 124.

- 165 -

to foreigners, so the possibility of becoming tenant farmers – the principal means that

immigrants used to access the land from the 1890s to the First World War – was also

restricted for the native born. Even in Córdoba, where just a third of the adult popula-

tion was foreign,171 the 1914 census found that foreigners made up 84 percent of

tenant farmers,172 as the native born had been denied access to the land, forcing them

to become landless labourers.

Native-born Argentines, who made up the vast bulk of the population before

the age of mass immigration began in the 1870s,173 were thus victims of the racism of

their ruling classes. Argentina’s liberal state builders had held the country’s peasant-

ries in contempt because they had provided the social base for the Federalist strong-

men who ruled the country after independence. Inspired in part by the travelogues of

British visitors to the River Plate, the liberals argued that the barbarism of the ‘Amer-

ican’ countryside needed to be replaced by the civilisation of the ‘European’ city.174

In the words of Domingo Sarmiento, the most prominent exponent of this idea,

progress meant following the ‘immutable laws’ that saw ‘the strong races extermin-

ate the weak ones, civilised peoples displace the savages from the land’, making it

necessary for the new Argentine state to continue what the Spanish empire had

begun: ‘absorb, destroy, exterminate’.175 Juan Bautista Alberdi, the main architect of

the 1853 constitution, put it more subtly with the famous phrase ‘to govern is to

populate’. As he explained:

If the population of six million Anglo-Americans that the United States of Americahad begun with, instead of growing with immigrants from free and civilised Europe,had been populated with Asiatic Chinese or Indians, or with Africans, or Turks,would it be the same country of free men as today? There is no land so favoured thatit could, by its own virtue, turn weeds into wheat. Good wheat can be born from badwheat, but not from barley.

To govern is to populate, but without forgetting that to populate can mean toinfest, brutalise, enslave, if the transplanted or migrated population, in place of

171. Calculated from CNC, Tercer censo, III, pp. 113-15.172. Calculated from ibid., V, p. 838.173. Argentines made up 82 percent of the population recorded by the 1869 census. Superintendente

del Censo, Primer censo, pp. 636-37, Tabla 3.174. These liberals had been exiled under Rosas, so much of their understanding of Argentina came

from the travelogues written by the British and other foreign visitors. See A. Prieto, Los viajerosingleses y la emergencia de la literatura argentina, 1820-1850, Buenos Aires, 1996. On theirracism, see Shumway, Invention of Argentina, pp. 139-45.

175. D.F. Sarmiento, ‘Investigaciones sobre el sistema colonial de los españoles, por J.V. Lastarria’, inidem, Obras, II, Buenos Aires, (1844) 1885, p. 214, author’s translation. This theme would betaken up at greater length in idem, Conflictos y armonías de las razas en América, Buenos Aires,(1883) 1915.

- 166 -

being civilised, is backwards, poor, corrupt. Why wonder that, in this case, therewould be those who would think, with reason, that to govern is to depopulate?176

Following such logic, the liberals believed that promoting European immigration was

a means to develop the country by improving its racial stock. Under the PAN, posit-

ivism – a belief in the social application of ‘scientific’ theories of race – would

become the dominant ideology of the new national ruling class. Prior to the First

World War, even though the mixed race probably continued to make up around half

of the country’s population, the positivists claimed that Alberdi’s dream had been

realised, as Argentina had become a European nation. In this way, much of the popu-

lation was excluded from Argentina as an imagined community.177

For the ideologues of the oligarchic state, denying the existence of Argen-

176. Alberdi, Bases y puntos, p. 15, author’s translation.177. José Ingenieros, for example, claimed that in ‘the most civilised countries and regions of South

America ‘Europeanisation’ is already a realised fact, superimposing modern culture and economyon the medieval inheritance that colonialism left us’. J. Ingenieros, ‘Las ideas sociológicas deSarmiento’, in Sarmiento, Conflicto y armonías, pp. 38-39, author’s translation. He would backthis claim up with figures that showed the mixed race and Indians falling from 81 percent of thecountry’s total population in 1852 to 22 percent in 1914, with the white population rising fromthree to 74 percent. Idem, Sociología argentina, 7th ed., Buenos Aires, 1918, pp. 451, 453. Mosthistorical accounts of racism in Argentina at the beginning of the twentieth century have unfortu-nately accepted such claims as fact, agreeing that ‘massive European immigration had reduced toa small number the proportion of blacks and other ethnic minorities in the population’. E.A.Zimmermann, ‘Racial Ideas and Social Reform: Argentina, 1890-1916’, Hispanic AmericanHistorical Review, 72:1, 1992, p. 45. In the words of another, Argentina ‘had become a nation ofpredominantly European stock’. A. Helg, ‘Race in Argentina and Cuba, 1880-1930: Theory,Policies, and Popular Reaction’, R. Graham, ed., The Idea of Race in Latin America: 1870-1940,Austin, 2010, p. 38. That this assumption is wrong can be seen in demographic studies. Mortara,for example, estimated that from 1841 to 1940 immigrants and their descendants, who can betaken as equivalent to the ‘white’ population, accounted for 58 percent of total populationgrowth, forming around 54 percent of the total population in 1940. G. Mortara, ‘Los factoresdemográficos del crecimiento de las poblaciones americanas en los últimos cien años’, Revista deEconomía y Estadística, 4:1-2, 1942, pp. 19-20. This suggests that prior to the First World Wararound half of the population was still mixed race. Recent studies of Argentina’s DNA havesimilarly demonstrated the extent of the country’s Indian heritage. In the words of Daniel Corach,one of the country’s leading geneticists, ‘[w]e have 60 percent of the population with Amerindiangenetic components. That is, with indigenous antecedents’. Interviewed in L. Moledo, ‘Lahistoria también se escribe en los genes’, Página/12, 10 August 2010, online at http://www.pagina12.com.ar/diario/ciencia/19-54853-2005-08-10.html (accessed 8 November 2013),author’s translation. Also see D. Corach, M. Marino, and A. Sala, ‘Relevant Genetic Contributionof Amerindian to the Extant Population of Argentina’, International Congress Series, 1288, 2006;M.C. Bobillo et al, ‘Amerindian mitochondrial DNA haplogroups predominate in the populationof Argentina: Towards a first nationwide forensic mitochondrial DNA sequence database’, Inter-national Journal of Legal Medicine, 124:4, 2010; D. Corach et al, ‘Inferring Continental Ances-try of Argentineans from Autosomal, Y-Chromosomal and Mitochondrial DNA’, Annals ofHuman Genetics, 74:1, 2010; and M.L. Catelli et al, ‘The Impact of Modern Migrations onPresent-Day Multi-Ethnic Argentina as Recorded on the Mitochondrial DNA Genome’, BMCGenetics, 12:77, 2011, online at http://www.biomedcentral.com/1471-2156/12/77 (accessed 8November 2013).

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tina’s mixed race population had the great advantage of making the losers from the

long boom disappear. The interior’s peasantries in particular had lost out because the

PAN’s promotion of railways had undermined their cottage industries. Until the

1880s peasants had still been able to use women’s textile production to supplement

incomes from agriculture.178 Even though their cloths and blankets had been

displaced from the Littoral’s markets by imports following independence, peasant

women had been able to supply most the interior’s own urban markets thanks to the

protection from imports given to them by the high costs of overland transportation,

combined with tariffs on imported cloths. The census data compiled in Table 4.4

show that in 1869 the first national census found 94,882 textile workers in Argentina,

with 95 percent of them located in the interior regions, where they made up 19

percent of the labour force. A better guide to who they were comes from a sample of

100,944 individual returns from that census:179 the 4,871 textile workers aged 14 and

over in the sample were overwhelmingly female (97 percent), based in the interior

(96 percent), living in the province where they were born (93 percent), rural (88

percent), and illiterate (95 percent).180 They were, then, much of the female half of

the interior’s rural poor.181 In Argentina, as in other parts of the periphery prior to the

long boom, poor rural women were heavily involved in textile production.182

The railways undermined the interior’s textile producers by permitting

cheaper factory-made goods to flood their markets. As can be seen in Table 4.4, the

178. D.J. Guy, ‘Women, Peonage, and Industrialization: Argentina, 1810-1914’, Latin AmericanResearch Review, 16:3, 1981, pp. 67-72. For a case study, see E. Hermitte and H.S. Klein, ‘Creci-miento y estructura de una comunidad provinciana de tejedores de ponchos: Belén, 1678-1869’,Documento de Trabajo 78, Centro de Investigaciones Sociales, Instituto Torcuato Di Tella, 1972.

179. The computer-coded sample was originally described in J.L. Somoza and A.E. Lattes, ‘Muestrasde los dos primeros censos nacionales de población, 1869 y 1895’, Documento de Trabajo 46,Centro de Investigaciones Sociales, Instituto Torcuato Di Tella, 1967. More recently Somoza andLattes’ raw data was made available as part of the IPUMS-International Census MicrodataHarmonization Project. See R. McCaa, M.R. Haines, and E.M. Mulhare, ‘Argentina: The FirstNational Historical Census Microdata’, in P.K. Hall, R. McCaa, and G. Thorvaldsen, eds., Hand-book of International Historical Microdata for Population Research, Minneapolis, 2000. Thedata are online at http://www.hist.umn.edu/~rmccaa/data/argentine_censuses_19thc.zip (accessed1 September 2013).

180. By way of comparison, the equivalent figures for all 59,473 people aged 14 and over in the fullsample were: 50 percent female, 50 percent based in the interior, 67 percent living in the provincewhere they were born, 62 percent rural, and 70 percent illiterate.

181. The sample suggests that a third of all rural women aged 14 and above in the interior wereemployed in textiles.

182. See, for example, N. Owen, ‘Textile Displacement and the Status of Women in Southeast Asia’,D. Ma, ed., The Pacific World: Lands, Peoples and History of the Pacific, 1500-1900, XII,Textiles in the Pacific, 1500-1900, Aldershot, 2005.

- 168 -

Table 4.4Argentina’s Textile Workers, 1869-1914

Total FederalCapital

OtherLittoral Centre West North South

(a) Number of workers1869 94,882 78 4,759 49,256 17,562 23,227 n.a.1895 39,725 538 1,101 18,574 11,140 8,246 1261914 30,980 2,528 1,018 14,860 5,836 6,610 128

(b) % of total occupations1869 11.1 0.1 1.6 22.6 14.1 18.4 n.a.1895 2.4 0.2 0.2 7.3 6.7 4.3 2.01914 1.0 0.2 0.1 3.1 2.6 2.2 0.4

Note: In 1869, the figures are for all those who declared occupations. In 1895 and 1914 theyare for those aged 14 and above. Textile workers include the following census occupations:

1869: blanqueadores; cordeleros, hiladores é hiladoras; tejedores y tejedoras; pelloneros;tintoreros; torcedores de lana, seda, etc.

1895: cordeleros, cabulleros, etc; tejedores; tintoreros.

1914: cardadores de lana; cordeleros; fabricantes de tejidos; hiladores, tejedores, tellaristas;tintoreros.

For the composition of the regions, see Table 4.2.

Sources: See Table 4.3.

number of textile producers fell significantly after the arrival of the railways: from

94,882 in 1869 to 30,980 in 1914;183 in the interior they fell from 19 to three

percent – a clear indication of deindustrialisation. The authors of the 1895 census

were in no doubt as to why this was happening. ‘Until 1869’, they wrote, referring to

textiles, ‘having no railways in the interior, and with high [internal] transportation

costs, a great proportion of the population consumed these products, which could

rival the prices of similar goods from abroad: today, the competition due to the relat-

ively low freight rates has made the consumption of domestic products fall, and

therefore retired from this profession many of those who used to engage in it’.184 The

railways thus took away one of the main sources of income that the interior’s rural

poor had traditionally depended upon, as handicraft textile production was displaced

by cheaper imports from abroad, as well as, although to a far lesser extent, goods

183. This fall is slightly exaggerated because the 1869 census includes child workers, whereas the1895 and 1914 only recorded the occupations of those aged 14 and over. However, only sixpercent of textile workers in the smaller sample were below 14 years old, so applying thatpercentage to the figure of 94,882 textile workers would still suggest a fall from 89,189 in 1869.

184. Comisión Directiva, Segundo censo, II, p. cxliv, author’s translation.

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made in the Littoral’s factories.185 This deindustrialisation is largely missing from the

optimistic accounts of Argentina’s industrial growth in the late nineteenth century.186

Nor was there sufficient growth in other industries to provide permanent

employment for the interior’s growing population. Even though much has been made

in the optimistic historiography of the growth of sugar and wine in the interior,187

these industries actually provided little in the way of permanent employment. Hence,

by 1914, there were around 14,000 adults permanently employed in sugar mills and

another 15,000 in wineries,188 which together was equivalent to just three percent of

the interior’s workforce, whereas textiles had previously employed 19 percent. The

benefits of growing the raw materials for these new industries were limited,

moreover, because of the highly restricted access to land. What smallholding there

was tended to be dominated by immigrants, so the native-born, especially men,

mainly participated in the new industries as day labourers, temporarily employed on

an oligarch’s plantation at harvest time, often under conditions of debt bondage.189

For this reason, the percentage of day labourers in the interior’s workforce increased

from 15 percent in 1869 to 26 percent in 1914.190 Unable to supplement their famil-

ies’ income with textile production, native-born women, meanwhile, were forced to

seek more precarious, and less autonomous, employment, particularly in the service

sector.191 Many of the coercive labour laws that the provincial oligarchies had previ-

ously depended upon to secure a supply of domestic servants could, as a result, be

185. Rocchi implies that the interior’s cottage industries were undermined by the Littoral’s industrial-isation, with imports having a secondary role. Rocchi, ‘Péndulo de la riqueza’, p. 49. However,the authors of the 1914 census report estimated that just 23 percent of the country’s demand fortextiles was met by domestic production. CNC, Tercer censo nacional, VII, p. 69. Given that thiswas the most important of the interior’s pre-railway-era cottage industries, it seems that Rocchihas exaggerated his case.

186. In his detailed study of Argentina’s industrialisation, Rocchi has denied that the country had anysignificant handicraft tradition, as ‘Argentine industry [...] started almost from scratch, and itsfactories rose like chimneys in a desert’. Rocchi, Chimneys in the Desert, p. 26. According toRocchi, ‘Córdoba’, for example, ‘did not have a large handicraft tradition’. Ibid., p. 138. To putthis claim in perspective, the census found that textile producers alone made up 13 percent ofCórdoba’s workforce in 1869, which then fell to one percent in 1914. Calculated from the samesources as Table 4.3. Such deindustrialisation was, by contrast, noted in the older, more pessim-istic literature, but the census data do not appear to have been analysed systematically. See, forexample, S. Bagú, Evolución histórica de la estratificación social en la Argentina, Buenos Aires,1969, pp. 29-30.

187. For example, Llach, ‘Wealth of the Provinces’; and Hora, Historia económica, pp. 236-44.188. Calculated from CNC, Tercer censo nacional, VII, pp. 395-96.189. Balán, ‘Migraciones, mano de obra’; Guy, ‘Rural Working Class’; and Salvatore, ‘Labor

Control’.190. See Table 4.3.191. Guy, ‘Women, Peonage’, pp. 72-76.

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abolished from the 1890s onwards.192

Argentina thus began the twentieth century in a paradoxical position: it was a

land-abundant country with widespread landlessness. As has been argued here, this

was for three reasons. First, public policy ensured that landownership became

increasingly concentrated, which restricted access to the land, so the country attrac-

ted those immigrants who would be willing to farm it as tenants, while those who

sought landownership went elsewhere. Accordingly, hundreds of thousands of

unskilled Southern European labourers arrived, but then found it more difficult to

become tenants as their numbers swelled, forcing them to join the floating popula-

tion. Second, further limitations were placed on the capacity of the native born to

access the land as tenants due to landowners’ preference for immigrants. Third,

cheaper imports undermined women’s textile production, which had previously

allowed the interior’s peasantries to supplement their incomes through agriculture,

and the new industries that did emerge provided relatively little permanent employ-

ment. The combination of concentrated landownership, ethnic discrimination, and

deindustrialisation were therefore the three main factors that limited progress for

much of the population.

Widespread landlessness then constrained Argentina’s intensive growth,

preventing it from attaining the same level of development as the European

offshoots. A restricted access to the land meant that the expanding frontier’s safety-

valve effect was muted, so surplus labour accumulated. Hence, in Argentina

unskilled manual labourers came to make up 30 percent of the labour force by the

end of the long nineteenth century,193 whereas in Canada they were around 17

percent,194 and in the United States 20 percent.195 This suggests that as Southern

Europeans continued to arrive in Argentina, the lack of access to the land prevented

192. See J.R. Scobie, Secondary Cities of Argentina: The Social History of Corrientes, Salta, andMendoza, 1850-1910, Stanford, 1988, pp. 200-03.

193. From the 1914 census, including the following: jornaleros; peones de campo; peones. As in Table4.3.

194. From the 1911 census. CSO, Fifth Census of Canada, VI, Occupations of the People, Ottawa,1915, xxvi, xxx, Tables 19 and 24.

195. From the 1910 census, including the following: laborers, except farm and mine; farm laborers,wageworking. From Bureau of the Census, Historical Statistics, I, pp. 139, 144, Series D182,D192, D603. If mineworkers are also included (ibid., I, p. 143, D479), it increases to 22 percent,although presumably many skilled workers would have been included in that category. Similarly,Australia’s 1911 occupational census did not distinguish sufficiently between skilled andunskilled workers, so a similar calculation cannot be made. See MSHA, Census of the Common-wealth of Australia, III, Melbourne, 1914, pp. 1298-325.

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the expanding frontier from absorbing the increased labour supply to the same degree

as in those countries where public policy provided land for settlers. Without the fron-

tier to act as a safety valve, the floating population then grew, which put downward

pressure on wages due to the greater labour supply. Wages were, as a result, consider-

ably below the levels of the other European offshoots – wages of unskilled building

labourers in Buenos Aires, for instance, were less than half the level of their equival-

ents in New York,196 so capitalists had less incentive to invest in labour-saving

machinery, since it was cheaper to hire more unskilled labour when necessary.197

Labour productivity accordingly remained below the more developed countries, so

incomes were lower, which restricted consumption levels, thereby limiting the size of

the domestic market for manufactured goods. Industrialisation, for this reason, was

modest: in 1913 Argentina’s industrial output per capita was approximately half the

Australian level, a fifth the Canadian level, and less than a tenth of the US level.198

There would consequently be little scope for Fordism in Argentina.199

Paradise Gained?Even at the beginning of the twentieth century, when a previous generation of optim-

ists was celebrating Argentina’s progress, there were still those who advanced a more

pessimistic vision.200 For instance, Juan B. Justo, the Socialist Deputy for the Federal

Capital, argued that the oligarchic state had depressed incomes by promoting mass

immigration from Europe at the same time as it encouraged the concentration of

landownership.201 In doing so, Justo observed, the oligarchic state had unwittingly

implemented a programme originally proposed by Edward Gibbon Wakefield, a Brit-

196. See Chapter 5, page 212, Table 5.7.197. For the case of farmers, see Adelman, Frontier Development, ch. 7.198. As in Chapter 3, page 112, these are rough estimates from Bairoch, ‘International Industrializa-

tion Levels’, pp. 302, 330, Tables 12 and 15; and Frankema and Visker, ‘Reversal of Fortune’,pp. 76, 86, Tables 1 and 5. For further evidence on the relatively low level of industrialisation inArgentina, based on census data, see H. Willebald and L. Bértola, ‘Uneven Development PathsAmong Settler Societies, 1870-2000’, in C. Lloyd, J. Metzer, and R. Sutch, eds., Settler Econom-ies in World History, Leiden, 2013, pp. 117-20.

199. See Chapter 3, pages 107-08, for a discussion of the nineteenth-century origins of Fordism in theUnited States.

200. See T. Halperín Donghi, ‘The Argentine Export Economy: Intimations of Mortality, 1894-1930’,in G. di Tella and D.C.M. Platt, eds., Political Economy of Argentina 1880-1946, New York,1986.

201. Justo, Obra parliamentaria, p. 18. On Justo, see Halperín Donghi, ‘Argentine Export Economy’,pp. 50-52.

- 172 -

ish diplomat, who in the first half of the nineteenth century had been concerned that

social hierarchy would be undermined in Britain’s land-abundant colonies, leading

him to propose that land be made artificially expensive.202 As Justo explained in a

speech to the National Congress in 1913:

The theorist of capitalist colonisation, an English author called Wakefield, came upwith the idea that the lordly owners of the Australian soil needed to do something topopulate their country. He said to them: If you do not change your line of conduct,you will never have manpower available here; men, as soon as they arrive, will findso much free land within reach, to be worked immediately by their hands, that it willallow them to make an independent life, without the need to subject themselves tothe yoke of the wage. So I advise you: you must oblige every immigrant to accumu-late his own funds through wage labour by only making public lands available at anartificial price.203

Even though these policies had been discarded in the Australian colonies soon after

they achieved dominion status in the 1860s,204 Justo believed that they had, in effect,

been applied in Argentina. He continued:

Here things have been done in this way, not only because [selling public lands] wasa source of fiscal resources, but also because it was an easy way to satisfy all thegovernment’s favourite little clients, so the public land has been squandered. Thereis not, Mr President, one little piece of land that could be given freely and easily tothe immigrant who wanted to work as an autonomous producer.205

The problem, then, for Justo, was that immigration had depressed wages (and, there-

fore, living standards) because of the concentration of landownership – an argument

that Aldo Ferrer and other pessimistic historians also made,206 and that has been reit-

erated here.

Where this chapter has added most to the pessimistic vision of Argentina at

the beginning of the twentieth century is in explaining how it got there. The chapter

has contended that Argentina was shaped by the boom in its terms of trade, which

was far greater than has previously been supposed. Argentina’s terms of trade prob-

ably improved by at least 2,000 percent from the 1780s to the first decade of the

202. Justo was probably familiar with Wakefield’s ideas through K. Marx, Capital: A Critique ofPolitical Economy, 4th ed., New York, 1906, ch. 38. Also see R. Grant, ‘Edward Gibbon Wake-field, England and ‘Ignorant, Dirty, Unsocial, ... Restless, More than Half-Savage’ America’,Comparative American Studies, 1:4, 2000, pp. 471-87.

203. Justo, Obra parliamentaria, p. 18, author’s translation.204. See Weaver, Great Land Rush, pp. 23-24.205. Justo, Obra parliamentaria, p. 18, author’s translation.206. Ferrer, Argentine Economy, esp. p. 116. Also see the discussion in Chapter 1, pages 35-36.

- 173 -

twentieth century. As Burgin originally maintained,207 this massive terms-of-trade

boom drove the civil wars that racked the River Plate for decades after independence,

as it allowed the land-abundant Littoral to prosper, while making the land-scarce and/

or landlocked interior stagnate. Only during the second half of the nineteenth century

would British investment facilitate the formation of a unified state by financing a

railway network that augmented the federal government’s capacity to intervene in the

provinces, thereby enabling it to buttress its supporters among the provincial ruling

classes. The oligarchic state that then formed would prevent Argentina from realising

its potential because it excluded much of the population from the country’s progress,

especially by encouraging the increasing concentration of landownership – a point

that optimistic historians have often missed by confusing the division of the largest

estates with a more egalitarian land distribution.

The implication of this analysis is that the presence of the relatively land-

scarce interior prevented Argentina from fulfilling its potential as a land-abundant

country. A North American-style white-egalitarian democracy was impossible in

Argentina because the interior’s peasantries had to be excluded from politics, since,

as in other parts of the poor periphery, they were losing out from the long boom. For

this reason, Argentina lacked the kind of social consensus that made democratisation

possible in North America. Rather, the oligarchic state restricted access to the land,

which muted the safety-valve effect of the expanding frontier, thus inhibiting the

kind of intensive growth that the European offshoots experienced. Chapter 5 will

verify this through a comparative assessment of the country’s living standards at the

beginning of the twentieth century.

Appendix 4.1: Argentina’s Terms of Trade, 1780-1938This appendix describes how the new part-proxy estimate of Argentina’s terms of

trade was calculated. It begins by discussing exchange rates, then the hide price

series used, the export price index as a whole, the proxy import price index, and

finally the end results. In describing the calculations in some detail, the goal of this

appendix is to facilitate reproduction, as reproducibility should be a basic element of

good research. An attempt is made to fully disclose, then, what has been done to the

207. Burgin, Economic Aspects, esp. ch. 1.

- 174 -

data to arrive at the results reported in this chapter. This goal is further advanced by

Tables DA.6 and DA.11-17 in the Data Appendix, which reproduce the data

discussed herein.

Exchange RatesBoth Argentina’s export price index and the export price indices of its trade partners

had to be converted to a common currency. The British pound sterling was used

because it was the main international currency of the nineteenth century. For the

trade partners included in the import price index, this was relatively straightforward:

Brazil’s export prices were already given in sterling; the US dollar exchange rate

comes from Lawrence Oliver’s series in the Historical Statistics of the United

States;208 France, Germany, and Italy’s exchange rates were taken from Markus

Denzel’s Handbook of World Exchange Rates up to 1914;209 thereafter they were

calculated from Oliver’s dollar exchange rates.210 They are reproduced in Table DA.6

in the Data Appendix.

For Argentina it is more challenging to arrive at a consistent exchange rate

series due to the changes in its currency over the course of the long nineteenth

century.211 Prior to the 1820s it is especially difficult because there are few available

series. It is therefore necessary to approximate exchange rates by looking at the silver

content of the pesos used in Buenos Aires and the market price of silver in London.

This has become the standard practice in the existing literature,212 and it is replicated

here. Reassuringly, this procedure leads to exchange rates that are similar to the first

reports of the rates actually paid, which come from the correspondence of British

merchants for 1816-21.213 From then until 1913 the exchange rates come from the

Buenos Aires business press, which provides the exchange rates used to convert

Argentina’s export prices to sterling from the 1820s until 1913;214 then the exchange

208. Officer, ‘Dollar–Sterling’ and ‘Bilateral Exchange Rates’, Series Ee618 and Ee636.209. Denzel, Handbook of World Exchange Rates, pp. 15-28, 42-43.210. Officer, ‘Bilateral Exchange Rates’, Series Ee625, Ee626, Ee629, and Ee636.211. See Álvarez, Temas de historia, pp. 80-124; and Denzel, Handbook of World Exchange Rates, pp.

463-67.212. For example, Allen, Murphy, and Schneider, ‘Colonial Origins’.213. As compiled in V.B. Reber, ‘British Mercantile Houses in Buenos Aires, 1810-1880’, PhD diss.,

University of Wisconsin, 1972, p. 313, Table 21.214. As compiled in J. Schneider, O. Schwarzer, and M.A. Denzel, Währungen der Welt, VII, Latein-

amerikanische Devisenkurse im 19. und 20. Jahrhundert, Stuttgart, 1997, pp. 212-18.

- 175 -

rates come from official compilations of market rates during 1914-33, and then from

official exporter and importer exchange rates during 1934-38.215 All these exchange

rates are reproduced in Table DA.11 in the Data Appendix.

Wholesale Prices of HidesOf all the price series included in Argentina’s export price index, the two for hides

were the most important because they were included from the beginning. Indeed,

during 1780-1829, hides are the only good in the index since they are the only one

for which, so far, a price series is available. Fortunately, they accounted for 70 to 80

percent of merchandise exports during this period,216 so the lack of price series for

other goods is not of major concern, given that such a coverage is generally

considered sufficient to construct an index.

Historians have typically depended on price series from the North Atlantic

core countries to measure the prices of Argentine hides. Following their lead, it

proved possible to identify five sources for hide prices in three core countries:

1) London: Monthly prices for Buenos Aires hides (presumably dry) for

1790-1840, as compiled by Arthur Gayer, Walt Rostow, and Anna

Schwartz.217 The prices are CIF (or 'in bond' prices), so they do not include

the import taxes charged on arrival in Britain.

2) Hamburg: Annual prices of Buenos Aires dry hides for 1814-45 and for

Buenos Aires and Montevideo salted hides for 1843-70, as compiled by Al-

fred Jacobs and Hans Richter.218

3) London: Quarterly prices for River Plate dry hides for 1818-1852, as com-

215. From M. Balboa, ‘La evolución del balance de pagos de la República Argentina, 1913-1950’,Desarrollo Económico, 12:45, 1972, p. 160.

216. W. Parish, Buenos Ayres and the Provinces of the Rio de la Plata, 2nd ed., London, 1852, , pp.353, Table 1.

217. A.D. Gayer, W.W. Rostow, and A.J. Schwartz, microfilmed supplement to The Growth and Fluc-tuation of the British Economy 1790-1850, I and II, Oxford, 1953; as compiled by D.S. Jacks,K.H. O’Rourke, and J.G. Williamson, ‘Commodity Price Volatility and World Market Integrationsince 1700’, Review of Economics and Statistics, 93:3, 2011, pp. 800-813; with the databaseavailable online at http://www.sfu.ca/~djacks/data/publications/Britain,%20Commodity%20Prices,%201790-1850, %20monthly.xlsx (accessed 3 May 2013).

218. A. Jacobs and H. Richter, Die Großhandelpreise in Deutschland von 1792 bis 1934, Berlin, 1935,pp. 68-69. The series for dry hides was also reproduced in J.C. Chiaramonte, Mercaderes delLitoral: Economía y sociedad en la provincia de Corrientes en la primera mitad del siglo XIX,Mexico, DF and Buenos Aires, 1991, p. 216, Cuadro 8.

- 176 -

piled by Tulio Halperín Donghi from the London Mercantile Price Current.219

4) Boston: Annual prices of Buenos Aires dry hides for 1840-91, as compiled by

Thomas Proctor for the ‘Aldrich Report’ on US wholesale prices.220

5) London: Annual prices of River Plate dry hides for 1846-1938 and for River

Plate salted hides for 1855-1938, as compiled by Augustus Sauerbeck and the

editor of the Statist.221 Again, the prices are CIF (or 'in bond').

These hide price series are reproduced in Table DA.12 in the Data Appendix.

While such prices have generally been used in the existing literature, they can

be highly misleading due to the great price convergence that occurred during the long

nineteenth century, as was discussed in Chapter 2. Domestic price series were there-

fore compiled instead. Unfortunately, such series are less common, and are some-

what fragmentary. In total, seven sources were found, although they need to be

treated carefully because there are complications regarding weights and measures.

Specifically, the unit used to measure hides was traditionally the pesada, which

consisted of 35 libras (Spanish pounds) of dry hides and 60 libras of salted hides,

until the metric system was adopted in the 1880s. Each libra (lb) weighed 0.4594

kilos (kgs).

The first three sources found were:

1) Zacharías Moutoukias’ compilation of the units and value in pesos of hides

exported, resulting in unit values for 1779-96.222

2) A report presented by British merchants to Woodbine Parish, the new British

consul, in 1824, giving periodic wholesale prices in reals for a 35 lb pesada of

dry hides during 1810-24, as well as monthly prices for a 35 lb pesada of dry

hides and a 60 lb pesada of salted hides for 1821-23.223

3) Julio Broide’s compilation of monthly paper peso wholesale prices, collated

from the periodical British Packet and Argentine News. Broide gives various

219. Halperín Donghi, ‘Expansión ganadera’, p. 65.220. US Senate, Wholesale Prices, Wages, and Transportation, II, Washington, DC, 1893, p. 141.221. Beginning with A. Sauerbeck, ‘Prices of Commodities and the Precious Metals’, Journal of the

Statistical Society of London, 49:3, 1886, p. 640.222. Z. Moutoukias, ‘Crecimiento en una economía’, p. 804, Cuadro 3.223. Anon., ‘Report on the Trade’; and idem, ‘Precios corrientes’, p. 60.

- 177 -

series: a 35 lb pesada of best quality ox hides for 1829-40; a 35 lb pesada of

best quality ox hides for export to North America for 1840-51; a 35 lb pesada

of best quality ox hides for export to Spain for 1840-51; and a 60 lb pesada of

salted cow hides for 1829-51.224

These series are reproduced in Table DA.13 in the Data Appendix.

For Moutoukias’ series, it was assumed that the units of hides exported

referred to pesadas, with dry and salted hides amalgamated. Fortunately, the British

merchants’ report suggests that there was little difference in price between a 35 lb

pesada of dry hides and a 60 lb pesada of salted hides at the beginning of the 1820s,

so it can be assumed that the unit values derived from Moutoukias’ series can be

taken as representative of the evolution of the prices of pesadas of dry hides up to

then. To test this assumption, the various dry-hide price series were compared to Juan

Carlos Garavaglia’s series for the prices of bulls in Buenos Aires. As shown in Figure

A4.1, both increased greatly, although the price of bulls did not rise quite as fast as

hides, which should be expected because the bull’s meat would not have risen so

dramatically during this period given that both export and domestic markets for beef

remained limited. Linking Moutoukias’ series with the British merchants’ series

probably presents, therefore, an accurate picture of the evolution of dry-hide prices.

Four other sources covering the second half of the long nineteenth century

and the interwar period were then identified:

4) Juan Álvarez’ monthly wholesale prices in gold pesos of 100 kg of salted

hides for 1863-1913, collated from the Buenos Aires Stock Exchange bullet-

in.225 Álvarez converted the prices to a 100 kg basis on the assumption that

they referred to a pesada of 60 lb, equivalent to 27.564 kg, except for July to

December 1880, when, according to the bulletins of those months, the pesada

weighed 66 lb (30.32 kg), and from January 1881 to November 1885, when it

weighed 64 lb (29.4 kg).226

5) Roberto Cortés Conde, Tulio Halperín Donghi, and Haydée Gorostegui de

224. J. Broide, ‘Evolución de los precios’, pp. 41-43, 50, Cuadros 16-18, and 22.225. Álvarez, Temas de historia, pp. 212-14.226. Ibid., p. 215.

- 178 -

Figure A4.1Prices of Bulls and Dry Hides in Buenos Aires, 1780-1848

1

10

100

1000

1780 1790 1800 1810 1820 1830 1840 1850

Bulls

Hides (M)

Hides (P)

Hides (B)

Reals, log scale

Note: Prices of bulls are reals per head; hides are in reals per 35 lb pesada. There were eightreals per peso.

Sources:

Bulls: Garavaglia, ‘Economía rural’; the underlying data were kindly provided by ProfessorGaravaglia.

B: Broide, ‘Evolución de los precios’, pp. 41-43, Cuadros 16-18.

M: Moutoukias, ‘Crecimiento en una economía’, p. 804, Cuadro 3.

P: Anon., ‘Report on the Trade’, p. 42; and idem, ‘Precios corrientes’, p. 60.

For the hide prices, see Table DA.13 in the Data Appendix.

Torres’ wholesale prices in gold pesos per ton of dry and salted hides for

1864-1906, collated from the Buenos Aires Stock Exchange bulletin, the

yearbook of the Argentine Rural Society, and the national press.227 Cortés

Conde et al appear to have assumed that a pesada of dry hides was equivalent

to 22 lb while a pesada of salted hides was equal to 76 lb.228 Exactly why they

assumed this is unclear, and it seems more likely that the prices they drew

227. Cortés Conde, Halperín Donghi, and Gorostegui de Torres, ‘Evolución del comercio’, p. 78.228. They write that one metric ton of dried hides equals ‘100 hides’, while one ton of salted hides

equals ‘28.57 hides’ (ibid., p. 78). Presumably, by ‘hide’ they are referring to a pesada, so accord-ing to this logic, a pesada of dry hides weighed 10 kg (or 22 libras) and a pesada of salted hides35 kg (or 76 libras).

- 179 -

Figure A4.2Two Series of Salted Hide Prices, 1864-1906

0

50

100

150

200

250

300

350

1860 1870 1880 1890 1900

Cortés Conde et al

Cortés Conde et al adjusted*

Álvarez

o$s per ton

* Cortés Conde et al’s series multiplied by 1.27 (that is, 76 divided by 60).

Sources: Álvarez, Temas de historia, pp. 212-14; and Cortés Conde, Halperín Donghi, andGorostegui de Torres, ‘Evolución del comercio’, p. 78. For the series, see Table DA.14 in theData Appendix.

upon were based on the traditional weight of 35 lb for a pesada of dry hides

and 60 lb for a pesada of salted hides. Indeed, by assuming 22 lb and 76 lb,

Cortés Conde et al have arrived at some strange results, as dry hides appear

far too expensive – more expensive than in their destination markets in the

core – and salted hides appear too cheap. Only if their series is adjusted to

reflect the old standard of 60 lb per pesada does it resemble Álvarez’ series, at

least until the weight of the pesada began to be adjusted prior to the adoption

of the metric system in the 1880s. Hence, Figure A4.2 illustrates how Cortés

Conde et al’s prices of salted hides are considerably below the prices given by

Álvarez until hide prices began to be quoted in kilos rather than pesadas in

the late 1880s. The adjusted series, by contrast, is similar.

6) The Dirección General de Estadística de la Nación’s (DGEN) series of whole-

sale prices in gold pesos per 10 kg for dry hides and per 100 kg for salted

- 180 -

hides.229

7) Unit values from the official trade statistics, which used wholesale prices to

value exports from 1907 onwards.230

These price series are reproduced in Table DA.14 in the Data Appendix.

Most of the hide price series, both from the core and Argentina, are shown in

Figures A4.3 and A4.4.231 As can be seen, the series are fragmentary, so it was neces-

sary to join them to make single series for dry and salted hides. In the final export

price index for dry hides, the following series were used: Moutoukias (series a in

Figure A4.3) for 1790-96; the British merchants (b) for 1810-20; their monthly series

(c) for 1821-23; Broide’s best quality (d) for 1829-39; Broide’s best quality for

export to North America (e) for 1841-51; Cortés Conde et al’s adjusted series (g) for

1864-79; their unadjusted series (f) for 1890-1906;232 and the official unit values (i)

for 1907-38. The gap in the series, 1880-89, was interpolated exponentially. For

salted hides, meanwhile, the British merchants’ monthly series was used for 1821-23

(series a in Figure A4.4); Broide for 1829-51 (b); Álvarez for 1864-1906 (e); and the

official unit values for 1907-38 (f).

The Export Price IndexThe export price index was calculated as a chained geometric Laspeyres index,

which is a shorthand means to approximate a chained Fisher index when annual

quantity data are lacking, as in this case.233 Ten separate subperiods were calculated,

then they were spliced together using the geometric mean of their overlapping peri-

ods.234 The weights assigned to the 31 different goods in each subperiod can be seen

in Table A4.1.235 They were assigned based on the values of goods exported in the

indicated years, according to Argentina’s trade statistics. Up to 1913, only 13 goods

229. DGEN, Extracto estadístico, pp. 204-05.230. For useful compilations, see Bunge, Intercambio económico, ch. 11; Tornquist, Economic Devel-

opment, pp. 167-72; and Vázquez-Presedo, Estadísticas históricas, II, pp. 194-221.231. Only the DGEN series were excluded because they are almost the same as the series of Alvarez

and the official trade statistics.232. By this point, hides were already being quoted in kilos, so there is no error in Cortés Conde et

al’s series.233. IMF, Producer Price Index, pp. 566, 593.234. As in the case of India’s terms of trade calculated in Appendix 2.2, the geometric mean has been

preferred due to its mathematical properties. See Hill and Fox, ‘Splicing Index Numbers’.235. When a series was not available for part of a subperiod, these weights were adjusted accordingly.

- 181 -

Figure A4.3Argentine Dry Hide Prices, 1780-1938

0 20 40 60 80

100 120 140 160 180 200 220

1780 1800 1820 1840 1860 1880 1900 1920 1940

a b

c

f

d e

g

h

i

£ per ton

(a) Buenos Aires

0 20 40 60 80

100 120 140 160 180 200 220

1780 1800 1820 1840 1860 1880 1900 1920 1940

j

k l

m n

(b) Core

Sources: The series included are:

a) Moutoukias’s unit values (Table DA.13, Series M).

b) The British merchants’ periodic series (Table DA.13, Series P.1).

c) Their monthly series (Table DA.13, Series P.2).

d) Broide’s best quality series (Table DA.13, Series B.1).

e) Broide’s best quality to Spain series (Table DA.13, Series B.2).

f) Broide’s best quality to North America series (Table DA.13, Series B.3).

g) Cortés Conde et al’s unadjusted series (Table DA.14, Series CHG.1).

h) Their adjusted series (Table DA.14, Series CHG.1a). To correct it, their series wasmultiplied by 0.63 (that is, 22 divided by 35).

i) The offical unit value series (Table DA.14, Series UV.1).

j) The Gayer et al series for London (Table DA.12, Series GRS).

k) The Jacobs and Richter series for Hamburg (Table DA.12, JR.1).

l) The Halperín Donghi series for London (Table DA.12, HD).

m) The Aldrich Report series for Boston (Table DA.12, P).

n) The Sauerbeck series for London (Table DA.12, S.1).

- 182 -

Figure A4.4Argentine Salted Hide Prices, 1821-1938

0 20 40 60 80

100 120 140 160 180 200

1820 1840 1860 1880 1900 1920 1940

£ per ton

a

b c

d

e

f (a) Buenos Aires

0 20 40 60 80

100 120 140 160 180 200

1820 1840 1860 1880 1900 1920 1940

g

h

(b) Core

Notes: The series included are:

a) The British Merchants’ monthly series (Table DA.13, Series P.3).

b) Broide’s series (Table DA.13, Series B.4).

c) Cortés Conde et al’s unadjusted series (Table DA.14, Series CHG.2).

d) Their adjusted series (Table DA.14, Series CHG.2b). To correct it, their series wasmultiplied by 1.27 (that is, 76 divided by 60)

e) Álvarez’ series (Table DA.14, Series A).

f) The official unit values (Table DA.14, Series UV.2).

g) Jacobs and Richter’s series for Hamburg (Table DA.12, JR.2).

h) Sauerbeck’s series for London (Table DA.12, S.2).

- 183 -

Tabl

e A4

.1W

eigh

ts in

Arg

entin

a’s E

xpor

t Pric

e In

dex,

178

0-19

38B

ase

year

:...

1822

1837

1851

1866

1881

1896

1910

1925

1938

Sub

perio

d:17

80 to18

22

1780 to

1837

1822 to

1851

1837 to

1866

1851 to

1881

1866 to

1896

1881 to

1910

1896 to

1925

1910 to

1938

1925 to

1938

Hid

es, d

ried

(178

0+)

1.00

000.

7347

0.69

710.

6501

0.34

380.

2658

0.05

790.

0382

0.01

820.

0093

Hid

es, s

alte

d (1

822+

)0.

0880

0.08

350.

0779

0.04

120.

0409

0.04

710.

0471

0.06

680.

0587

Bee

f, je

rked

(182

9+)

0.12

220.

1057

0.09

670.

0296

0.05

770.

0274

0.00

29Ta

llow

and

fat (

1833

+)0.

0435

0.03

560.

1348

0.07

630.

0275

0.02

480.

0293

0.02

290.

0103

Woo

l, di

rty (1

833+

) 0.

0116

0.07

810.

0164

0.40

390.

4899

0.35

070.

1633

0.08

400.

0998

Cat

tle (1

864+

)*0.

0193

0.02

100.

0899

0.01

30S

heep

ski

ns, d

irty

(186

4+)

0.02

420.

0858

0.08

710.

0453

0.02

460.

0063

0.00

75W

heat

(187

8+)

0.00

020.

1193

0.20

040.

2345

0.14

91M

aize

(187

9+)

0.00

780.

1487

0.16

720.

1418

0.14

67Fl

our (

1880

+)0.

0022

0.01

810.

0137

0.01

540.

0083

Lins

eed

(188

7+)

0.06

380.

1238

0.10

640.

1473

Goa

t ski

ns (1

893+

)0.

0070

0.00

36B

arle

y (1

910+

)0.

0004

0.00

360.

0149

Bee

f, ch

illed

(191

0+)*

0.00

330.

0853

0.13

52B

eef,

cons

erve

d (1

910+

)0.

0059

0.02

020.

0364

Bee

f, fro

zen

(191

0+)

0.09

530.

0581

0.02

71B

ran

(191

0+)

0.01

250.

0073

0.01

29B

utte

r (19

10+)

0.00

500.

0251

0.00

72O

ats

(191

0+)

0.02

260.

0204

0.01

84Q

uebr

acho

ext

ract

(191

0+)

0.01

230.

0220

0.02

80Q

uebr

acho

logs

(191

0+)

0.01

560.

0033

0.00

34R

ye (1

910+

)0.

0000

0.00

040.

0003

- 184 -

Tabl

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Bas

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8118

9619

1019

2519

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1780 to

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1822 to

1851

1837 to

1866

1851 to

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1910

1896 to

1925

1910 to

1938

1925 to

1938

Sug

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350.

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sour

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1822

, 183

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Par

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Bue

nos A

yres

, pp.

353

-54,

Tab

les 1

and

2.

1866

, 188

1, 1

896:

Cor

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perín

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and

Gor

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, pp.

66-

68 C

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: Bun

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p. 3

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1925

, 193

8: V

ázqu

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rese

do, E

stad

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rica

s, II

, pp.

194

-221

.

- 185 -

were included, largely due to the lack of price series, although that also reflected the

limitation of Argentina’s exports to a small number of goods. Prior to the First World

War, for example, the 13 pre-1910 goods accounted for almost 90 percent of

exports.236

Fortunately, compiling the other price series was considerably easier than for

hides because the weights and measures were more straightforward.237 The sources

were the same: Broide’s compilation for the 1820s to the 1840s; Cortés Conde et al’s

series for the 1860s to the 1900s; the official unit values from the 1900s to the 1930s.

All prices were then converted to sterling and metric tons prior to the calculation of

the export price index. Beef prices were the only major problem since it proved

necessary to use cattle prices as a substitute for the price of beef itself. All of the

underlying price series and the export price index are reproduced in Tables DA.15

and DA.16.

As a check for errors, the new export price index was compared with a previ-

ous index calculated by Héctor Diéguez for 1864-1938.238 The similarity between the

two, as seen in Figure A4.5, is reassuring, especially as they were calculated using

different methods. Whereas the new series is a chained geometric Laspeyres index,

the Diéguez series is a chained implicit arithmetic Paasche index, calculated in two

steps:

1) Several arithmetic Laspeyres export quantity indices were calculated, then

joined using ratio splicing at a single overlapping year.

2) The current value of exports, as estimated by Cortés Conde et al,239 was di-

vided by the export quantity index.

Given this quite different methodology, the similarities between the two series is

striking, even if they do diverge somewhat toward the end.

236. The 13 goods accounted for an average of 87 percent of exports during 1909-13. Calculated fromCortés Conde, Halperín Donghi, and Gorostegui de Torres, ‘Evolución del comercio’, p. 69,Cuadro 3.

237. See Álvarez, Temas de historia, ch. 2.238. Diéguez, ‘Crecimiento e inestablidad’.239. Cortés Conde, Halperín Donghi, and Gorostegui de Torres, ‘Evolución del comercio’.

- 186 -

Figure A4.5Two Export Price Indices for Argentina, 1864-1938

0

50

100

150

200

250

1860 1870 1880 1890 1900 1910 1920 1930 1940

1913 = 100

Dieguez

New

Note: Both indices are denominated in British pound sterling.

Sources:

Dieguez: Export price index in gold dollars calculated from Diéguez, ‘Crecimiento einestablidad’, pp. 340, 347, 349, Cuadros 10 and 18. Converted to British pounds using theUS dollar-sterling in Officer, ‘Dollar–Sterling’; and idem, ‘Bilateral Exchange Rates’, inCarter et al, Historical Statistics, Series Ee618 and Ee636; adjusted for the US dollar goldpremium during 1864-79 from Simon, ‘United States’, p. 633, Table 1.

New: See text and Table DA.16.

A Proxy Import Price IndexTo date, there are few domestic price series for Argentina’s main imports during the

nineteenth century, so to get a rough idea of the country’s terms of trade, it is neces-

sary to use proxy prices for imports. Traditionally, the standard practice, as seen in

Appendix 2.1, has been to use a British export price index as a proxy for peripheral

countries’ import prices. Here, by contrast, export price indices for six of Argentina’s

major trade partners – Brazil, Britain, France, Germany, Italy, and the United States –

were gathered, then combined into a chained geometric Laspeyres index, calculated

in the same way as Argentina’s export price index. With the exception of Brazil, the

export price indices were calculated by other scholars,240 then converted to sterling

- 187 -

Table A4.2Weights in Argentina’s Proxy Import Price Index, 1780-1938

Base year: 1825 1850 1870 1890 1910 1930

Subperiod:1780

to1850

1825to

1870

1850to

1890

1870to

1910

1890to

1930

1910to

1938Britain (1780+) 0.6250 0.4639 0.3674 0.5194 0.3727 0.2710United States (1790+) 0.1406 0.1031 0.0814 0.0836 0.1650 0.3016France (1809+) 0.0859 0.2577 0.3630 0.1786 0.1147 0.0823Brazil (1821+) 0.1484 0.1134 0.0955 0.0301 0.0310 0.0565Italy (1862+) 0.0619 0.0479 0.0778 0.1083 0.1277Germany (1880+) 0.0448 0.1105 0.2083 0.1608

Total: 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

Note: The year after each good indicates the first year of its export price index. The sum ofthe weights may not equal one due to rounding.

Sources:

1825 and 1850: Parish, Buenos Ayres, p. 361.

1870: R. Napp, La República Argentina, Buenos Aires, 1876, p. ii.

1890: Latzina, Estadística retrospectiva, pp. 220-23.

1910 and 1930: DGEN, Anuario del comercio exterior de la República Argentinacorrespondiente a 1937 y noticia sumaria del período 1910-1937, Buenos Aires, 1938, pp.lxxxviii-cv.

using the exchange rates described above. Brazil’s index was calculated as a chained

geometric Laspeyres index, using unit values from the country’s historical trade

statistics.241 In calculating Argentina’s proxy import price index, the weights assigned

to each country in each subperiod were based on Argentina’s trade statistics. The

weights can be seen in Table A4.2. In Table DA.17 in the Data Appendix the proxy

import price index is reproduced, together with the export price indices that underlie

it. It should be stressed that the result is a crude proxy for Argentina’s import prices,

above all because it does not take into account the effects of changing trade costs,

especially the price convergence that took place during the long nineteenth century.

240. Britain: Cuenca Esteban, ‘Rising Share’, p. 901, App. Table 1; Imlah, Economic Elements, pp.94-98, Table 8; and Feinstein, National Income, pp. T132-32, Table 61. France: M. Lévy-Leboyer, ‘L’héritage de Simiand: Prix, profit et termes d'échange au XIX e siècle’, RevueHistorique, 243, 1970, pp. 108-111, Table 5. Germany: W.G. Hoffmann, Das Wachstum derdeutschen Wirtschaft seit der Mitte des 19. Jahrhunderts, Berlin, 1965, pp. 606-09, Table 151.Italy: Federico et al, Commercio estero, pp. 228-29, Tabella 7b. United States: various seriescompiled in Irwin, ‘Exports and Imports’.

241. Nine goods were included. They were reweighted every 10 years according to the value of theirexports. Calculated from IBGE, Estatísticas Históricas do Brasil: Séries Econômicas Demo-gráficas e Sociais de 1550 a 1988, 2nd ed., Rio de Janeiro, 1990, pp. 345-56.

- 188 -

Figure A4.6New and Old Terms-of-Trade Estimates for Argentina, 1810-1938

1

10

100

1000

1780 1800 1820 1840 1860 1880 1900 1920 1940

1913 = 100, log scale

Ferreres

New

Sources:

Ferreres: Ferreres, Dos siglos, Series 8.1.7.

New: Calculated from the price indices in Tables DA.15 and DA.17.

ResultsIn Figure A4.6 the new part-proxy terms-of-trade estimate that results from these

export and import price indices is compared to what can be considered the standard

series, as reproduced in Orlando Ferreres’ statistical compendium.242 A logarithmic

scale has been used to facilitate comparisons between their rates of change. As can be

seen, up to around 1880, the new series increases substantially faster than the

Ferreres series, particularly immediately after independence in 1810. As discussed in

Chapter 2 and this chapter, this can be explained by the considerable price conver-

gence that occurred due to falling trade costs. After that process had finished, the two

series become similar, especially once Ferreres begins to use the official series,

which was calculated from Argentina’s own domestic prices from 1910 onwards.243

242. The series underlying it are the same as those used by Williamson, as described in Appendix 2.1,page 87. The only exception is for 1870-84, when it consists of Diéguez’ export price indexdivided by Britain’s export price index. See Ferreres, Dos siglos, p. 658.

243. On the calculation of the official series, see Bunge, Intercambio económico.

- 189 -

Table A4.3Three Estimates of Argentina’s Terms of Trade, 1780s-1900s

FerreresNew

Part-proxy Adj. part-proxy*1780s 6.4 3.91810s 39.7 18.5 11.51830s 68.3 44.8 31.01870s 76.8 79.0 68.61900s 100.0 100.0 100.0

Growth, %:1780s to 1900s 1,451 2,4851810s to 1900s 152 441 771

* Based on the assumption that Argentina’s import prices were 100 percent higher than thecore’s export prices until 1810, but then fell exponentially to 20 percent in the 1900s.

Note: All three estimates were referenced so that 1900-09 equals 100.

Sources: As in Figure A4.6.

Even this new part-proxy estimate is likely, however, to understate the magn-

itude of Argentina’s terms-of-trade boom because, as seen in Chapter 2, the peri-

phery’s import prices also converged with the core’s export prices during the long

nineteenth century. Using a proxy import price index therefore introduces a down-

ward bias into the trend of Argentina’s terms of trade. For this reason, Table 4A.3

gives a rough indication of what the terms of trade might look like if it were possible

to calculate an import price index using Argentina’s own prices. The Ferreres and the

new series are both shown as decadal averages, referenced so that 1900-09 equals

100; then, in the final column, the new part-proxy estimate is adjusted to reflect the

convergence in import prices, based on the assumption that high trade costs meant

that Argentina’s import prices were 100 percent higher than the core’s export prices

until independence in 1810, but then fell at a constant rate until they reached 20

percent of the core’s export prices in the first decade of the twentieth century. Such a

fall in trade costs is highly likely to have occurred, and in reality it was probably

even greater. The difference it makes can be clearly seen. Hence, whereas Ferreres’

series increases by 152 percent from the 1810s to the 1900s, the new part-proxy

estimate increases by 441 percent, and the adjusted part-proxy estimate increases by

771 percent. Looking further back, the adjusted part-proxy estimate suggests an even

greater boom, as it shows a 2,485 percent improvement from the 1780s to the

- 190 -

Figure A4.7Terms of Trade for Argentina and Indonesia, 1780-1938

1

10

100

1000

1780 1800 1820 1840 1860 1880 1900 1920 1940

1913 = 100, log scale

Indonesia

Argentina (Adj. part proxy)

Sources:

Argentina: See Table A4.2.

Indonesia: Korthals Altes, Changing Economy, XV, pp. 158-60. See Table DA.4.

1900s, compared to 1,451 percent in the unadjusted series. Argentina’s terms-of-trade

boom was, then, far greater than has previously been supposed.

Finally, lest these estimates seem improbable, in Figure A4.7 the adjusted

part-proxy series is compared to Indonesia’s terms of trade, which, as detailed in

Chapter 2, is the only own-price estimate for a peripheral country that reaches into

the first half of the nineteenth century. Figure A4.7 implies that the magnitude of the

terms-of-trade boom indicated by the adjusted part-proxy estimate is highly plaus-

ible, at least from the mid-1820s, when the Indonesian series begins. Were Indone-

sia’s terms of trade extended further back into the eighteenth century, moreover, it is

probable that its own boom would appear even greater, as the country’s commodities

were selling in Europe for around 400 percent of their export prices before the nine-

teenth century.244 This strongly reinforces, therefore, the argument made in Chapter

2: that prices from the core must not be used as proxies for prices in the periphery.

244. O’Rourke and Williamson, ‘When Did Globalisation Begin?’, p. 33, Figure 4.

- 191 -

Instead, further research is required into the price records of the peripheral countries

themselves. This appendix has contributed to this task by compiling and processing

the available evidence for Argentina’s export prices.

- 192 -

Chapter 5

The ‘Golden Age’ Myth

I see the imitation of Europe, and nothing that reveals America to me.Domingo Sarmiento, Facundo: Civilisation and Barbarism1

It is commonly believed that by the end of the long nineteenth century Argentina was

a rich country. One historian, for instance, exuberantly declares that ‘[t]hese were the

glory days for Argentina: the country seemed at last to have shed its history and

seated itself at the table of the richest nations in the world’.2 The question then

becomes why it subsequently declined. As a prominent New Economic Historian

puts it: ‘[o]nce one of the richest countries in the world, Argentina has been in relat-

ive economic decline for most of the twentieth century’3 – the ‘Argentine paradox’

then becomes the question of why a rich country became a poor country.4 Yet, as this

chapter demonstrates, the starting point for this research agenda is wrong. Through a

comparative assessment of Argentina’s living standards prior to the First World War,

the chapter concludes that, in short, there was no ‘golden age’ in which Argentina

rivalled the world’s most developed countries.

In comparing Argentina to various other countries at the beginning of the

twentieth century, this chapter adopts a broad concept of living standards as ‘human

development’. Reflecting this, the chapter examines comparable indicators for polit-

ical institutions, public welfare, and national incomes.5 It finds that in no case were

Argentina’s levels of human development comparable to the most advanced coun-

tries: its political institutions lagged far behind those of the Anglo-Saxon countries;

1. Sarmiento, Facundo: Civilisation, p. 38.2. Rocchi, Chimneys in the Desert, p. 87.3. Taylor, ‘External Dependence’, p. 907.4. See the discussion in Chapter 1, pages 18-19.5. See UNDP, Human Development Report, p. 10; also see Chapter 1, pages 37-38.

- 193 -

its levels of public welfare were inferior to those of Northern Europe, at around the

same levels as Southern Europe; the chapter shows that measuring incomes presents

considerable methodological challenges, but most likely they were higher in Argen-

tina than Italy and Spain, especially for skilled workers, but they trailed those of

Northern Europe, let alone its offshoots. Argentina should not, therefore, be

considered one of the world’s most developed countries. As will be discussed further

in Chapter 6, this chapter thus verifies this dissertation’s pessimistic revision of

Argentina’s long nineteenth century.

Living StandardsTo the greatest possible extent, living standards in Argentina prior to the First World

War will here be compared to major countries of Northern Europe, the prosperous

European offshoots, more or less backward Southern European countries, and Argen-

tina’s largest South American neighbours. In interpreting these comparisons, particu-

lar attention will be given to the European offshoots because they, like Argentina,

were land-abundant countries, and there has been a substantial comparative literature

that has sought to explain why Argentina failed to reach their heights.6 This chapter

contributes to that literature by placing Argentina’s failure within the context of the

new metanarrative of global divergence that was outlined in Chapter 3, as well as its

initial application to Argentina in Chapter 4. The result is a far simpler explanation of

Argentina’s failure than is sometimes offered. In short, it is argued here that Argen-

tina’s failure was primarily due to a lack of democracy, which both resulted from and

reinforced the greater unevenness of its development. For this reason, the assessment

will begin with a comparative analysis of Argentina’s political development.

Political InstitutionsIn terms of its political institutions, Argentina was less advanced than the most

developed countries. Table 5.1 illustrates this using two databases that attempt to

provide comparable measures of political development. The first is the Polity IV

6. Most notably, D. Denoon, Settler Capitalism: The Dynamics of Dependent Development in theSouthern Hemisphere, Oxford, 1983; D.C.M. Platt and G. di Tella, eds., Argentina, Australia andCanada: Studies in Comparative Development 1870-1965, Oxford, 1985; C.E. Solberg, ThePrairies and the Pampas: Agrarian Policy in Canada and Argentina, 1880-1930, Stanford, 1987;Schwartz, In the Dominions; Schedvin, ‘Staples and Regions’; Adelman, Frontier Development;and Willebald and Bértola, ‘Uneven Development Paths’.

- 194 -

Table 5.1International Political Indicators, c. 1900-13

Author: Polity IV VanhanenPeriod: 1909-13 1900-09

Indicator: Autocracy* Democracy* Polity** Competition*** Participation†South America

Argentina 2 3 1 17 2Brazil 4 1 -3 9 2Chile 2 5 3 29 4

Northern EuropeBritain 0 8 8 50 10France 0 8 8 68 22Germany 3 5 2 35 8

Southern EuropeItaly 4 3 -1 32 4Spain 0 6 6 21 8

European offshootsAustralia 0 10 10 62 19Canada 0 9 9 48 18United States 0 10 10 46 17

* An 11-point scale, from zero to 10.

** A 21-point scale, from -10 to 10, calculated as the democracy indicator minus theautocracy indicator.

*** Smaller parties’ share of the vote in national elections, calculated as 100 minus thepercentage share of the largest party.

† Percentage of the population that voted in national elections.

Sources:

Polity IV Project, ‘Political Regime Characteristics and Transitions, 1800-2010’, datasetonline at http://www.systemicpeace.org/inscr/p4v2011.xls (accessed 20 January 2013).

Vanhanen: T. Vanhanen, Prospects of Democracy: A Study of 172 Countries, London, 1997,pp. 34, 251, 257-58, 260-61, 262, 266.

Project database, which measures the degrees of both autocracy and democracy on

11-point scales by taking into account the ways in which political leaders are

recruited, the constraints on their power, restrictions on the population’s participation

in politics, and the competitiveness of that participation. The 11-point scale for auto-

cracy is then subtracted from the 11-point scale for democracy, in order to arrive at a

21-point scale for the overall quality of the country’s polity. These indicators have

been compiled for virtually every independent state in the world, based on accounts

of their political evolution since the nineteenth century.7 As can be seen in Table 5.1,

7. This project started with T.R. Gurr, ‘Persistence and Change in Political Systems, 1800-1971’,

- 195 -

compared to the other countries considered here, Argentina had a moderate level of

autocracy. This was because it had a strong president whose term was nevertheless

fixed at six years, and whose successor was appointed by a directly elected Electoral

College. However, Argentina also had a fairly low level of democracy due to parti-

cipation in elections being limited by the lack of a secret ballot and the restriction of

the vote to male Argentines. Tatu Vanhanen’s measures of political competition and

participation confirm this negative assessment. Hence, according to his estimates,

parties other than the PAN took just 17 percent of votes in Argentina during the

1900s, while only two percent of the population voted. On all measures, then, Argen-

tina lagged far behind the most politically advanced countries, which were found in

Northern Europe and the European offshoots.

This political backwardness reflected the slow pace of reform in Argentina.

Until the Sáenz Peña Law of 1912, voting, for example, was carried out verbally in

public, so victory in elections largely depended upon the use of patronage, intimida-

tion, and fraud. In much of the interior, the PAN’s heartland, this meant that elections

could be controlled by their provincial governors, who used patronage to persuade

local military commanders and magistrates to support their candidates, particularly

by promising them employment for family members in the government bureaucra-

cies.8 In Buenos Aires elections were more competitive, but for much of the second

half of the nineteenth century that competition normally entailed the use of gangs to

march selected voters to the polls to publicly declare for one candidate, while block-

ing voters who had been herded to the polls by a rival politicians’ gang.9 In the 1890s

new political parties, most notably the UCR,10 but also the Socialists,11 did provide

considerable opposition in provincial and national legislatures, yet even then parti-

cipation in politics was limited by the restriction of the vote to native-born and natur-

alised adult males, which excluded women and much of the immigrant-dominated

American Political Science Review, 68:4, 1974, pp. 1482-504. Since then, it has become widelyused by social scientists. See the Centre for Systemic Peace, online at http://www.system-icpeace.org (accessed 20 January 2013).

8. Rock, State Building, pp. 69-72. For an analysis of the provincial elite communities that formedin Buenos Aires as a result, see S. Bower, ‘Political and Socio-Economic Elites: The Encounterof Provincials with Portenos in Fin-De-Siêcle Buenos Aires’, Americas, 59:3, 2003, pp. 379-403.

9. Cullen Crisol, ‘Electoral Practices’, pp. 24-30, 34-43; and Sabato, Many and the Few, pp. 56-58.10. Alonso, Between Revolution, ch. 5.11. J. Adelman, ‘Socialism and Democracy in Argentina in the Age of the Second International’,

Hispanic American Historical Review, 72:2, 1992, pp. 211-38.

- 196 -

middle classes. In the Federal Capital just 17 percent of the adult population were

qualified to vote,12 in large part as a result of only two percent of foreign-born males

having taken up citizenship;13 the rest remained unnaturalised because the bureau-

cratic process was long, they would have risked being conscripted, foreigners were

already treated well, and there was, in any case, little to gain in being able to vote,

given the lack of a secret ballot. Only after the Sáenz Peña Law made elections fairer

in 1912 by establishing the secret ballot did the rate of naturalisation increase

significantly.14

Earlier reform of this electoral system was inhibited due to the overrepresent-

ation of the interior provinces in the National Congress. One of the compromises in

the 1853 constitution was that the federal government would have a bicameral legis-

lature with each of the 14 provinces plus the capital receiving two seats in the Senate,

and 50 seats to be assigned proportionally to their populations in the Chamber of

Deputies, with the number of seats expanded and their distribution recalculated

according to each new national census; the President of the Republic was nominated

for a six-year term by a directly elected Electoral College, in which each province

and the Federal Capital received twice the number of its total senators and deputies.15

This system favoured the interior not only due to its provinces receiving the same

number of seats in the Senate as the larger Littoral provinces, but more importantly

because the censuses were only taken sporadically. Thus, until the results of the 1895

census were implemented in 1898, the Electoral College reflected the distribution of

the population according to the 1869 census, without any allowance for the shift in

population that had occurred since then.16 The consequent overrepresentation of the

interior provinces can be seen in Panel (a) of Figure 5.1, in which the provinces’

share of the total population in 1895 is shown on the horizontal axis, and their share

in the Electoral College around that time is shown on the vertical axis. It can be seen

that the interior provinces, represented by the hollow dots, were overrepresented

since they are above the diagonal line of perfectly proportional representation,

12. Calculated from CNC, Tercer censo, III, pp. 18-21.13. Calculated from ibid., I, p. 202; and ibid., II, Población, Buenos Aires, 1916, p. 417.14. C. Solberg, Immigration and Nationalism: Argentina and Chile, 1890-1914, Austin, 1970, pp.

42-43, 124-25; and Moya, Cousins and Strangers, p. 489, fn. 18.15. Representantes del Pueblo de la Nación Argentina, ‘Constitución de 1853’, pp. 272-73, 280-81,

Articles 34, 42, and 78.16. Llach, ‘Wealth of the Provinces’, pp. 119-20.

- 197 -

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- 198 -

whereas Buenos Aires, Santa Fe, and the Federal Capital were underrepresented, as

they were considerably below it. This meant that Argentina’s political institutions

overrepresented the interior provinces where peasantries had been excluded from

politics during the state-formation process, as was seen in Chapter 4. It was, by

contrast, the underrepresented Littoral region, especially its middle classes, which

provided most of the financial and electoral support for the new political parties that

were pressuring the PAN for electoral reform.17

Only when the number of deputies was adjusted according to the findings of

the 1895 census did the balance of power swing towards the Littoral. Previously

Buenos Aires, the Federal Capital, and Santa Fe had just 30 percent of the votes in

the Electoral College, but after the census results were implemented in 1898 they

possessed 44 percent, so their representatives were almost able to choose the Presid-

ent on their own.18 This was what a Deputy from Córdoba had described in 1897 as

the threat of ‘two provinces and a city’ electing the President – a threat that had

inspired the interior provinces to block the holding of a new census for so long.19

With their numbers increased, the Littoral’s Deputies were able ensure that there was

no such delay in holding the next census. As shown in Panel (b) of Figure 5.1, when

the 1914 census was taken the distribution of votes had not become as dispropor-

tional as in the 1890s. In the meantime, the Littoral’s influence in the Electoral

College had, moreover, ensured the victory of Luis Sáenz Peña as President in 1910.

Sáenz Peña then pushed through an electoral reform two years later that would

finally introduce the secret ballot, bringing some long-delayed democratisation.20 The

length of the delay nevertheless meant that Argentina’s political development still

lagged that of the most advanced countries. In Australia, for example, the secret

ballot had been introduced in the 1850s, and Canada had followed in 1874.21 This

17. Gallo and Sigal, ‘Formación de los partidos’, pp. 212-22; O. Cornblit, ‘La opción conservadoraen la República Argentina’, Desarrollo Económico, 14:56, 1975, pp. 619-21; and Alonso,Between Revolution, pp. 11, 159-60.

18. Calculated from Botana, Orden conservador, p. 88, Cuadro 1.19. Quoted in H. González Bollo, ‘Sobre la amenazante mayoría de dos provincias y una ciudad: Los

tres primeros censos demográficos y su impacto político en Argentina (1853-1920)’, EstadísticaEspañola, 52:174, 2010, p. 320, also pp. 318-19; and Llach, ‘Wealth of the Provinces’, pp.138-39.

20. The importance of the census in facilitating electoral reform has often been missed. For example,Botana, Orden conservador, ch. 7; and Rock, State Building, ch. 5. It has, however, featuredprominently in recent analyses of the PAN’s economic policies. See Llach, ‘Wealth of theProvinces’, ch. 4; and Gerchunoff, Rocchi, and Rossi, Desorden y progreso, ch. 8.

21. P. Brent, ‘The Australian Ballot: Not the Secret Ballot’, Australian Journal of Political Science,

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head start had allowed such countries to institutionalise democracy to a far greater

degree than in Argentina.

Public WelfareMoving on to public welfare, health is arguably its most important aspect. In the

literature on human development, life expectancy at birth has been the most

commonly used indicator.22 Yet historians have often lacked data on life expectancy,

so instead they have increasingly used heights as an indicator of ‘biological well

being’.23 In deference to that trend, Table 5.2 begins by reproducing the data

compiled by Joerg Baten and Matthias Blum for 10 of the 11 countries under review

here. They show that Argentine men born in the first decade of the twentieth century

grew to be taller than Frenchmen, but shorter than other Northern Europeans and

men in the European offshoots. Interpreting these results is problematic, however,

because it is less than clear that heights should be considered as a proxy for welfare,

biological or otherwise.24 For Argentina the use of heights is particularly problematic

given that human growth is heavily influenced by meat consumption, as, in the words

of a survey of the biological literature, ‘[a]mong single nutrients affecting growth,

protein is probably the most important’.25 It may just be, then, that Argentines were

reasonably tall as a result of having to survive on a fairly monotonous diet of beef.26

41:1, 2006, p. 42.22. UNDP, Human Development Report, p. 12.23. For an overview, see R.H. Steckel, ‘Heights and Human Welfare: Recent Developments and New

Directions’, Explorations in Economic History, 46:1, 2009.24. Among developing countries in the second half of the twentieth century, for instance, there was

little correlation between adult heights and infant mortality rates in the year of birth, and nocorrelation with GDP per capita. A. Deaton, ‘Height, Health, and Development’, Proceedings ofthe National Academy of Sciences, 104:33, 2007.

25. K. Silventoinen, ‘Determinants of Variation in Adult Body Height’, Journal of Biosocial Science,35:2, 2003, p. 273

26. For this reason, studies of heights have not been used to support the pessimistic revision ofArgentina’s long nineteenth century given in this dissertation. They have found that there was adecline in average heights from the 1780s through to the 1800s, notable increases from the 1810sto the 1830s, then decline during the 1840s and ‘50s, followed by stagnation up to the First WorldWar. R.D. Salvatore, ‘Heights and Welfare in Late-Colonial and Post-Independence Argentina’,in J. Komlos and J. Baten, eds., The Biological Standard of Living in Comparative Perspective,Stuttgart, 1998, pp. 106-10; idem, ‘Stature Decline and Recovery in a Food-Rich ExportEconomy: Argentina 1900–1934’, Explorations in Economic History, 41:3, 2004, pp. 238-42;idem, ‘Heights, Nutrition, and Well-Being in Argentina, ca. 1850-1950: Preliminary Results’,Revista de Historia Económica, 25:1, 2007, pp. 60-66; J. Baten, I. Pelger, and L. Twrdek, ‘TheAnthropometric History of Argentina, Brazil and Peru During the 19th and Early 20th Century’,Economics and Human Biology, 7:3, 2009, pp. 320-24; and J. Baten and M. Blum, ‘AnAnthropometric History of the World, 1810-1980: Did Migration and Globalization Influence

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Table 5.2International Health Indicators, c. 1900-13

Indicator: Heights (cm)* Life expectancy at birth, years**Source: Baten & Blum Clio Infra CraftsPeriod: 1900-09 1910 1913

South AmericaArgentina 168.2 44 46Brazil 166.5 ... 31Chile ... 32 30

Northern EuropeBritain 169.4 54 53France 166.8 51 50Germany 169.2 45 49

Southern EuropeItaly 165.6 47 47Spain 164.6 41 42

European offshootsAustralia 172.3 ... 59Canada 169.9 53 53United States 170.0 52 52

* The figures are for both sexes.

** Average adult height of people born in this decade.

Sources:

Life expectancy: ‘Crafts, ‘Human Development Index: Some Historical Comparisons’, p.307, Table 2; and Clio Infra, available online at http://www.clio-infra.eu/datasets/indicators(accessed 15 October 2013).

Heights: J. Baten and M. Blum, ‘Growing Tall but Unequal: New Findings and NewBackground Evidence on Anthropometric Welfare in 156 Countries, 1810–1989’, EconomicHistory of Developing Regions, 27:Sup1, 2012, p. 566-85; underlying data available at http://www.clio-infra.eu/datasets/indicators (accessed 15 October 2013).

Estimates of life expectancy, a more traditional measure, therefore provide a less

ambiguous measure of health.

Two sets of life-expectancy estimates for men and women at birth before the

First World War are reproduced in Table 5.2. Both suggest that life expectancy was

Country Trends?’, Journal of Anthropological Sciences, 90, 2012, pp. 3-4. These findings havebeen interpreted as indicating that a far more pessimistic interpretation of Argentina’s nineteenthcentury is warranted, with the notion ‘that the period 1880-1914 was a ‘golden age’’ seemingparticularly dubious. Salvatore, ‘Heights, Nutrition’, p. 82. However, it is notable that similartrends can be seen in the US data, where the explanation mainly appears to be due to peopleshifting their diets away from meat and dairy products towards grains, rather than poorer nutri-tion per se. See J. Komlos, ‘Anomalies in Economic History: Reflections on the AntebellumPuzzle’, Journal of Economic History, 56:1, 1996; also J. Baten and M. Blum, ‘An Anthropomet-ric History of the World, 1810-1980: Did Migration and Globalization Influence CountryTrends?’, Journal of Anthropological Sciences, 90, 2012, pp. 3-4.

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Table 5.3Life Expectancy at Birth in Argentina, 1913-15

Argentines Foreigners

(a) Female

Buenos Aires 50 56Centre-Littoral 47 54West (Cuyo) 40 47Northeast 37 44

(b) MaleBuenos Aires 47 51Centre-Littoral 45 51West (Cuyo) 39 44Northeast 37 41

Note: The entities included in the regional groupings are:

Buenos Aires: Buenos Aires and the Federal Capital.

Centre-Littoral: Entre Rios, Santa Fe, and Córdoba

West (Cuyo): San Juan and Mendoza.

Northeast: Tucumán, Salta, and Jujuy.

Source: Compiled from J.L. Somoza, La mortalidad en la Argentina entre 1869 y 1960,Buenos Aires, 1971, pp. 110-13, 117-20, 123-26, 130-33, 136-39.

not as high in Argentina as in the world’s most developed countries. At 46 years,

according to Nicholas Crafts’ estimates, Argentines’ life expectancy was above the

two South American countries (and far above the world’s poorest: in India, for

instance, life expectancy at birth was around 20 years during this period),27 but it was

only around Southern European levels, which were considerably below the 50 plus

years achieved in Northern Europe and the European offshoots.

Uneven development across regions and ethnicities again explains why life

expectancy in Argentina did not reach the same level as the most developed coun-

tries. Table 5.3 reproduces a demographer’s estimate of life expectancy at birth for

men and women across four regions of Argentina during 1913-15.28 As should be

expected, they indicate that people lived far longer in the Littoral, and everywhere

foreigners lived longer than the native born. This disparity meant that a girl born

abroad who subsequently moved to Buenos Aires could expect to live 56 years,

whereas a native-born girl in the Northeast had a life expectancy of 37 years. The

27. Habib, ‘Studying a Colonial Economy’, p. 373, Table 2.28. These are probably the same estimates that underlie the Clio Infra and Crafts figures in Table 5.2.

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former could thus expect to live as long as a woman in the most developed countries,

but the latter had a life expectancy that was a long way below Southern European

levels.

Such regional and ethnic disparities were not only due to the lower incomes

of the interior and the native born, but also to the inferior provision of public goods

outside Argentina’s capital city. For example, a survey included in the 1914 census

found that the National Waterworks had assets of £26.2 million in the Federal

Capital, compared to just £3.6 million in the rest of the country.29 As an illustration,

this meant that in the Federal Capital it had assets of £16 for every inhabitant, but in

Córdoba, the country’s third city, it had just £5 per person.30 This difference reflected

the longstanding lack of interest of Córdoba’s provincial government in a sanitation

system,31 whereas in Buenos Aires varying combinations of provincial, municipal,

and federal governments had been investing in one since the 1870s.32 Such uneven

provision of public goods relating to health prevented Argentina as a whole from

having a high average life expectancy at birth. In Figure 5.2 this is illustrated by

comparing estimates of life expectancy in the two cities with those of the world’s

most developed countries. It shows that while Buenos Aires approached the levels of

Britain and the United States by the First World War, in Córdoba life expectancy had

increased little since the late 1890s. Indeed, at just 35 years in 1909-13, average life

expectancy in Córdoba was far below Southern European levels, whereas in Buenos

Aires it had reached 48 years.33

Education similarly suffered from the uneven provision of public goods.

Hence, in 1914 the census found that 82 percent of the Federal Capital’s children

29. CNC, Tercer censo, X, p. 461. The National Waterworks was a public agency that had takencontrol of the country’s sanitation system in 1912. See A. Regalsky, ‘De Buenos Aires a lasprovincias: La construcción de una empresa pública de saneamiento en la Argentina, 1892-1930’,Desarrollo Económico, 50:199, 2010.

30. City populations from Tornquist, Economic Development, p. 20.31. A. Carbonetti, ‘La conformación del sistema sanitario de la Argentina: El caso de la Provincia de

Córdoba, 1880-1926’, Dynamis, 25, 2005; also M.C. Boixadós, Las tramas de una ciudad,Córdoba entre 1870 y 1895: elite urbanizadora, infraestructura, poblamiento, Córdoba, 2000,pp. 194-202.

32. Regalsky, ‘De Buenos Aires’, pp. 456-58.33. It is worth noting that these estimates are probably more reliable than the national life expectan-

cies used in Tables 5.2 and 5.3 because they are based on more concrete mortality data frommunicipal records. B. Ribotta, ‘Los niveles de mortalidad de la ciudad de Córdoba a principiosdel siglo XX: ¿Particularidad demográfica o deficiencia administrativa?’, in D. Celton, M. Ghir-ardi, and A. Carbonetti, eds., Poblaciones históricas: Fuentes, métodos y líneas de investigación,Córdoba, 2010, p. 213.

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Figure 5.2International Life Expectancy at Birth, 1870-1913

20

25

30

35

40

45

50

55

60

65

1870 1880 1890 1900 1910 1920

Years

Australia

Córdoba

Buenos Aires Britain*

USA

* England and Wales only.

Note: The series show estimated life expectancy at birth for males and females. Missing yearswere interpolated linearly.

Sources:

Australia: South Australia, Statistical Register of South Australia 1963-64, II, Adelaide, 1966,p. 47. Located through the Human Life-Table Database, online at http://www.lifetable.de(accessed 14 January 2013).

Britain: V. Kannisto, Life Table Collection, mimeo, n.d. Also located through the HumanLife-Table Database.

Buenos Aires (Federal Capital): M.S. Muller, La mortalidad en Buenos Aires entre 1855 y1960, Buenos Aires, 1974, pp. 88-91.

Córdoba (capital): D.S. Celton, ‘La mortalidad en la ciudad de Córdoba (Argentina) entre1869 y 1990’, Boletín de la Asociación de Demografía Histórica, 10:1, 1992, pp. 53-54.

United States: M.R. Haines, ‘Estimated Life Tables for the United States, 1850-1900’, NBERHistorical Paper 59, 1994, Appendix A; and F.C. Bell and M.L. Miller, ‘Life Tables for theUnited States Social Security Area 1900-2100’, Actuarial Study 116, Social SecurityAdministration, 2005, p. 162, Table 10.

aged 6 to 14 attended school, whereas just 55 percent did in the rest of the country; in

the Littoral outside the Federal Capital the attendance rate was 51 percent; in the

Centre, 58 percent; in both the North and the West, 62 percent; and in the South, 35

percent.34 Such regional disparities depressed Argentina as a whole below the levels

34. Calculated from CNC, Tercer censo, I, p. 178. Also see J.C. Tedesco, Educación y sociedad en la

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Table 5.4International Education Indicators, c. 1909-1913

Indicator: Primary school enrolment,% of 5-14 year olds

Literacy rate,%

Source: Benavot &Riddle Lindert Crafts

Period: 1910 1910 1913South America

Argentina 37 41 64Brazil 11 12 35Chile 39 43 63

Northern EuropeBritain 79* 73 96France 86 86 92Germany 73 76 97

Southern EuropeItaly 45 45 62Spain 35 47 52

European offshootsAustralia 89 89 96Canada 88 92 94United States 97 98 92

* England and Wales only.

Sources:

Literacy rates: Crafts, ‘Crafts, ‘Human Development Index: Some Historical Comparisons’,p. 307, Table 2.

Primary enrolment: A. Benavot and P. Riddle, ‘The Expansion of Primary Education,1870-1940: Trends and Issues’, Sociology of Education, 61:3, 1988, pp. 205-07; and P.Lindert, Growing Public: Social Spending and Economic Growth Since the EighteenthCentury, II, Further Evidence, Cambridge, 2004, pp. 122-27, Appendix Table A1, alsoavailable online at http://lindert.econ.ucdavis.edu/Docs/17/App._T._A1__primary_enrol.xls(accessed 5 February 2013).

of the world’s most developed countries. Two estimates of primary school enrolment

rates in 1910, reproduced in Table 5.4, both indicate that Argentina was far behind

Northern Europe and the European offshoots, at around the same level as Southern

Europe,35 while Crafts’ estimates of literacy rates tell a similar story.

Argentines’ relatively low level of schooling reflected the long delay in

constructing an adequate public education system. In the 1860s the liberal state

builders had sought to construct a nationwide education system, so in 1871 the

Argentina (1880-1900), Buenos Aires, 1970, pp. 177-79.35. These figures measure primary enrolment as the enrolment of 5-14 year olds, which explains

why they are lower than the enrolment levels of 6-14 year olds given above for Argentina’sregions.

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Figure 5.3International Primary School Enrolment, 1870-1913

0

10

20

30

40

50

60

70

80

90

100

1870 1880 1890 1900 1910 1920

Argentina

Italy

Spain

Britain

USA

Australia

%

Note: The series show the percentage of children aged 5-14 enrolled in school in 1870, 1880,1890, 1900, 1910, and (estimated) 1913. The figures for 1913 were estimated by interpolatinglinearly between 1910 and 1920.

Source: Lindert, Growing Public, II, pp. 122-27, Appendix Table A1.

federal government had begun to subsidise the construction, equipping, and running

of primary schools across the country.36 However, the money made available became

a considerable source of patronage, beginning when Nicolás Avellaneda, as Minister

of Education during 1868-1874, used the subsidies to build a personal following

among the governors of the interior provinces, who provided the necessary support

for him to succeed Sarmiento as president.37 Subsequently, providing scholarships

and comfortable teaching posts for family members of supporters continued to be a

major form of patronage. A reflection of this was the disproportionate amount of the

budget spent on secondary schooling, teacher training, and higher education, leading

to an underfunding of primary education.38 In a speech to Congress in 1913 Juan B.

36. J.E. Hodge, ‘The Formation of the Argentine Public Primary and Secondary School System’,Americas, 44:1, 1987, pp. 56-57.

37. Rock, State Building, p. 70.38. In 1910, for example, primary schooling only took about 30 percent of federal spending on

education. DGEN, Anuario: Correspondiente al año 1910, III, Buenos Aires, 1912, p. 180. Alsosee Tedesco, Educación y sociedad, pp. 189-91.

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Justo, the socialist Deputy for the Federal Capital, explained that this imbalance was

because ‘nepotism reigns in the public administration’.39 Denouncing this practice, he

continued:

It suits them very well being an instructor in a national college or a normal school[teacher-training college], while the school teacher is in a very poor situation. Andno man of importance would dare offer his protégé a school teacher’s post; so thatthe easiest positions are given to the most unskilled, the most uncultured: those ofthe upper reaches of the hierarchy. And so we see these establishments multiply, in acountry where we are lacking primary schools for 600,000 children.40

Thus, Argentina’s education system continued to suffer from a misallocation of

resources.

The oligarchic state did not, then, provide Argentina with the same levels of

public welfare as in the world’s most developed countries, with regional disparities

once more being crucial. In Buenos Aires City the municipal and federal govern-

ments became better at supplying public goods because the city’s prosperity gener-

ated an informed civil society that used the press to demand a better provision of

public services, thereby persuading the politicians from these regions to implement

reforms.41 It would be a mistake, nevertheless, to view this as representative of

Argentina as a whole. Outside the capital city, particularly in the interior, civil soci-

ety was far less developed, not least due to people being less literate. Patronage

accordingly remained the key to electoral success,42 which gave the provincial olig-

archies few incentives to increase the supply of public goods, other than to provide

positions for their supporters. The unevenness of Argentina’s development in this

way prevented it from being one of the world’s most developed countries in terms of

public welfare.

39. J.B. Justo, La obra parlamentaria del diputado socialista por la capital, Buenos Aires, 1913, p.146, author’s translation.

40. Ibid., p. 147, author’s translation. Also see Tedesco, Educación y sociedad, pp. 199-202.41. E.A. Zimmerman, Los liberales reformistas: La cuestión social en la Argentina (1890-1916),

Buenos Aires, 1995, esp. ch. 2. On the formation of the public sphere, see H. Sabato, ‘Citizen-ship, Political Participation and the Formation of the Public Sphere in Buenos Aires1850s-1880s’, Past & Present, 136, 1992; also idem, Many and the Few, ch. 2. On the centralrole of the press in the more competitive elections of Buenos Aires, see Cullen Crisol, ‘ElectoralPractices’, pp. 30-34; Sabato, ‘Citizenship, Political Participation’, pp. 151-53; and Yablon,‘Patronage, Corruption’, ch. 7.

42. For a detailed study of the case of Córdoba, see Chaves, Sufragio y representación, pp. 39-99.

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National IncomeArgentina’s relative national income is more difficult to assess. Even for much of the

twentieth century, reliable estimates of the country’s GDP, the standard measure of

national income, are in short supply, as was detailed in Appendix 1.1. Crucially, this

means that the standard methodology used to produce historical GDP estimates –

extrapolating back from recent purchasing-power-parity (PPP) benchmarks using

volume indices of GDP – is subject to large margins of error. This methodology was

pioneered by economists at the University of Pennsylvania, then popularised by

Angus Maddison.43 Those recent PPP benchmarks are calculated using statistics of

prices across countries, in order to adjust nominal GDP figures for differences in

price levels, resulting in an estimate in ‘international prices’. By extrapolating back-

wards from these benchmarks with a volume index, the Penn methodology should

produce, in theory, past GDP statistics in ‘constant international prices’ of the bench-

mark year. However, the accuracy of those historical estimates is entirely dependent

on the quality of the benchmark estimates and the volume indices, which are of poor

quality for the case of Argentina.

Some of the historical GDP statistics produced by the Penn methodology are

reproduced in Table 5.5. For the 11 countries under consideration here, Maddison’s

various estimates of their GDP per capita in 1913 have been referenced so that

Britain’s GDP per capita equals 100. All seem to indicate that Argentina’s past GDP

per capita was high, although this should be expected because, as was discussed in

Appendix 1.1,44 there is a downward bias in the trend of Argentina’s volume indices

due to the disproportional growth of the informal sector. What is more surprising, by

contrast, is the sheer variation in the estimates. Hence, by extrapolating backwards

from a 1980 benchmark, Maddison originally estimated that Argentina’s GDP per

43. B. Kravis, A. Heston, and R. Summers, World Product and Income: International Comparisonsof Real Product and Purchasing Power, Baltimore, 1978; A. Maddison, Monitoring the WorldEconomy 1820-1992, Paris, 1995; and idem, The World Economy, I and II, Paris, 2006. For thehistory of the methodology, see A. Maddison, ‘Quantifying and Interpreting World Development:Macromeasurement Before and After Colin Clark’, Australian Economic History Review, 44:1,2004. The state of the art is described in A. Deaton and A. Heston, ‘Understanding PPPs andPPP-based National Accounts’, American Economic Journal: Macroeconomics, 2:4, 2010; andR.C. Feenstra, R. Inklaar and M. Timmer, ‘The Next Generation of the Penn World Table’,Groningen Growth and Development Centre, 2013, online at http://www.rug.nl/research/ggdc/data/pwt/v80/the_next_generation_of_the_penn_world_table.pdf.

44. Pages 43-45.

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Table 5.5International GDP Per Capita, 1913

Britain = 100

Source: Maddison(1988)

Maddison(1994)

Maddison(1995)

Maddison(2006)

Benchmark: 1980 1985 1990 1990South America

Argentina 58 57 75 77Brazil 17 17 17 16Chile 41 42 53 54

Northern EuropeBritain 100 100 100 100France 63 66 69 71Germany 62 60 76 74

Southern EuropeItaly 58 50 50 52Spain ... 53 45 42

European offshootsAustralia 111 110 109 105Canada 90 85 84 90United States 123 117 105 108

Note: The figures show the country’s GDP per capita in 1913, referenced so that Britainequals 100. The benchmark refers to the PPP estimate from which the series are extrapolatedbackwards.

Sources: A. Maddison, The World Economy in the 20th Century, Paris, 1988, p. 19, Table 1.3;idem, ‘Explaining the Economic Performance of Nations, 1820–1989’, in W.J. Baumol, R.R.Nelson, and E.N. Wolff, eds., Convergence of Productivity: Cross-National Studies andHistorical Evidence, Oxford, 1994, p. 22, Table 2.1; and Maddison, Monitoring the World,pp. 23-24, Table 1-3; and idem, World Economy, II, pp. 438-39, 445, 466, 520, Tables 1b, 1c,2c, and 4c.

capita in 1913 was equivalent to 58 percent of British GDP per capita, which then

fell to 57 percent in a revision that extrapolated back from a 1985 benchmark, but

when Maddison switched to a 1990 benchmark his estimate shot up to 75 percent,

then rose further to 77 percent in the final and most widely used version of his data-

base. The same methodology thus produced a wide range of results: according to the

first pair of estimates, Argentina was around the level of Italy and Spain, but accord-

ing to the second pair, it was far above them, as well as being above France and

Germany. This gives an indication of the kinds of margin of error that afflict

Maddison’s numbers, irrespective of the overestimates of past GDP levels that will

result for countries, such as Argentina, where the informal sector has grown faster

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than the formal sector.45 It seems with good reason, then, that two of the leading

experts on the Penn methodology have concluded that ‘many of these numbers have

substantial uncertainty, and that extrapolations over long periods can easily lead to

results that make no sense’.46 Unfortunately, that did not stop Maddison, nor has it

prevented legions of historians from regularly using his numbers without questioning

their origins.47

Compared to GDP, wages are a less problematic means to assess past income

levels because wage data are relatively abundant, as are the data on consumer prices

that are needed to make them comparable across countries. By contrast, correctly

calculating GDP requires a mass of data on the output of (or expenditure on) a multi-

tude of different goods and services. Consequently, historians have increasingly

preferred to look at wages to evaluate past income levels.48 They have relied on two

main methodologies. The first is to deflate a country’s wages into a common PPP

currency, which becomes a benchmark from which they can extrapolate backwards

using a series for ‘real’ wages – in other words, the same Penn methodology that is

used to produce historical GDP estimates.49 The second methodology, pioneered by

Robert Allen, is to calculate ‘welfare ratios’ (WRs) by dividing wages by the cost of

a basket of goods that would have provided a subsistence-level standard of living for

a worker and his family.50 Table 5.6 summarises the results of both methodologies in

the existing literature, with the various estimates for the nine countries under consid-

eration again referenced so that the level in Britain equals 100. Jeffrey Williamson,

as can be seen, has produced the only estimate for Argentina, and it supports the

impression that it was one of the most developed countries in the world, with PPP

wages greater than in France and Germany. Yet those countries with more than one

estimate indicate why Williamson’s numbers should be treated with caution: the

range can be large. In the case of the United States, for example, workers’ incomes

45. This, most likely, would also apply to the other South American countries, as well as Italy andSpain. Their GDP per capita estimates shown in Table 5.5 would also be overestimated as aresult.

46. Deaton and Heston, ‘Understanding PPPs’, p. 33.47. On this problem, also see Jerven, ‘Unlevel Playing Field’.48. For example, Williamson, ‘Evolution of Global Labor’; Allen, ‘Great Divergence’; Allen et al,

‘Wages, Prices’; and Allen, Murphy, and Schneider, ‘Colonial Origins’.49. Most notably, see Williamson, ‘Evolution of Global Labor’.50. For the state of the art, see Allen, Murphy, and Schneider, ‘Colonial Origins’. Also see Chapter 3,

pages 100-02 and 115-17, for some of his results.

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Table 5.6International Real Wages, pre-First World War

Britain = 100

Author: Allen Allen et al Williamson ZamagniPeriod: 1909-13 1909-11 1909-13 1909-13 1905

Type: PPP* WR** WR*** PPP† PPP††South America

Argentina ... ... ... 89 ...Brazil ... ... ... ... ...Chile ... ... ... ... ...

Northern EuropeBritain 100 100 100 100 100France ... 62 ... 65 67-69Germany ... ... 73 84 64-70

Southern EuropeItaly ... 29-33 24 49 38-41Spain ... 43 ... 49 ...

European offshootsAustralia 140 ... ... 124 ...Canada 188-222 ... ... 196 ...United States 249-257 ... ... 160 117-125

* Wages for bricklayers in a major city in each country adjusted by price levels calculatedusing a British consumption basket. The cities are Manchester, Sydney, Toronto andVancouver, and Chicago and San Francisco. Ranges indicate the values for two cities.

** Welfare ratios for building labourers in major cities. The cities are London, Paris, Florenceand Milan, and Madrid.

*** Welfare ratios for building labourers in major cities. The cities are London, Milan, andLeipzig.

† Wages for unskilled labourers adjusted by price levels calculated using a multilateralconsumption basket.

†† Average national wages for industrial workers adjusted by price levels calculated using amultilateral consumption basket.

Sources: V. Zamagni, ‘An International Comparison of Real Industrial Wages, 1890-1913’, inScholliers, ed., Real Wages, p. 119, Table 5.4; R.C. Allen, ‘Real Incomes in the English-Speaking World, 1879-1913’, in G. Grantham and M. MacKinnon, eds., Labour MarketEvolution, London, 1994, p. 130, Table 6A.5; idem, ‘Great Divergence’, p. 416, Tables 1 and2; Williamson, ‘Evolution of Global Labor’, p. 184, Table A3.1; and Allen et al, ‘Wages,Prices’.

appear to have been somewhere between 117 and 254 percent of British workers’

incomes, which is quite a wide range! Even producing internationally comparable

wage levels thus entails major margins of error, so it would be inappropriate to rely

just on Williamson’s estimate to evaluate Argentina’s living standards.51 Rather, the

accuracy of Williamson’s estimate must be checked against the raw material.

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Table 5.7International Weekly Wages in Construction, c.1905-09

Labourer,s

Skilled,*s

Buenos Aires (1907)** 27-29 48-58Northern Europe

Berlin (1905) 26 33-40London (1905) 30 45Paris (1905) 25 39-44

European offshootsMontreal (1905) 42 62-102New York (1909) 70 94-117Sydney (1907)** 43 57-67

* Includes bricklayers, carpenters, and masons. In Buenos Aires, such trades were classifiedas oficiales.

** Monthly wages were calculated from daily wages, assuming a working week of six days.

Note: The wages are in British sterling. There were 20 shillings (s) per pound (£), and 12pennies (d) per shilling.

Sources:

Buenos Aires: Departamento Nacional de Trabajo (DNT), Boletín, 3, Buenos Aires, 1907, p.347.

Berlin: Board of Trade, Cost of Living in German Towns, London, 1908, p. 12.

London: idem, Cost of Living of the Working Classes, London, 1908, p. 27.

Paris: idem, Cost of Living in French Towns, London, 1909, p. 12.

Montreal: Board of Inquiry, Cost of Living, I, Ottawa, 1915, pp. 582, 584, 588.

New York: Board of Trade, Cost of Living in American Towns, London, 1911, p. 22.

Sydney: New South Wales, Official Year Book: 1907-08, Sydney, 1909, p. 485.

Wages themselves are the most basic building block of such a reassessment,

so Table 5.7 provides the nominal wages in shillings of construction workers in

Buenos Aires and six cities in Northern Europe and its offshoots around the years

1905-09.52 For Berlin, London, and New York, the data were collected by the British

51. Bunge also produced an early attempt to estimate the purchasing power of worker’s incomes inArgentina relative to other countries. He found that they were 91 percent the level of Britain, 88percent the level of France, 97 percent the level of Germany, and 65 the level of the UnitedStates. Bunge, Renta y riqueza, p. 275. The main problems with Bunge’s estimates are that (1)they are for family incomes, so they include child labour; (2) Argentina’s family income is from asample from Buenos Aires, where the social structure was unrepresentative of the rest of thecountry, as there were far more skilled workers in the capital; and (3) in estimating the pricelevels Bunge compared the rent of a single room in Buenos Aires with the rent of two roomseverywhere else.

52. The focus here will be on comparing incomes in Argentina with those in the more developedcountries because there is a shortage of good-quality data on South American and SouthernEuropean wages, prices, and rents. See, for example, V. Zamagni, ‘The Daily Wages of Italian

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Board of Trade; for the other four cities, they were taken from various government

publications. The construction sector has been chosen because the work was fairly

homogenous across countries, so the wages give a reasonably accurate indication of

the incomes of workers in the same occupations in each city. The range of wages for

skilled workers illustrates one of the problems with this exercise: wages varied

considerably, and it is now impossible to know what the average wage was. Never-

theless, in general it can be seen that unskilled labourers in Buenos Aires received

similar nominal wages to those in Northern Europe, while skilled workers received

somewhat more, although both received less than their counterparts in the European

offshoots. What data there are also reveal that wages were far greater in Buenos

Aires than in Southern Europe. In Italy in 1905, for instance, a skilled construction

worker earned about 14 shillings per week, and a labour earned nine shillings –

respectively just a quarter and a third of the Buenos Aires levels.53

Nominal wages in themselves are not enough to assess incomes, however,

due to variations in price levels in different places. Where prices are high, the

purchasing power of wages will be reduced; where prices are low, it will be raised.

Here this is particularly important because Buenos Aires was renowned for being an

expensive city, which suggests that ‘real’ wages were lower than the nominal figures

imply. For example, an English-language guide to Argentina published in 1911

provided a description of the high cost of living.54 It stated:

[T]he retail price of meat in Buenos Aires and other cities has increased enormouslyof recent years from rather obscure causes, but the rise of population is one. A kilo-gramme of meat, for which seven or eight years ago twenty or twenty-five centavos(4d. or 5d.) would have been paid, cannot now be purchased for less than forty orforty-five centavos (9d. or 10d.), or a hundred per cent. more, and this, it may beremarked, is not a prime cut, but the poorest part of the animal, which the workingclasses buy. Furthermore, the quality is far inferior today to what it was formerly,and in every sense therefore meat has become extremely dear in Argentina. Indeed,one Argentine newspaper once rather caustically remarked that, taking all thingsinto account, meat in the Smithfield Market [in London] is often cheaper than inBuenos Aires, notwithstanding the fact that Smithfield depends largely on Argentinafor a great part of its supplies. Bread prices in the capital have been affected to someextent by what is to all intents and purposes a milling monopoly, though municipalordinances (regulating the bakehouses and the sale of bread) and threats of labour

Industrial Workers in the Giolittian Period (1898-1913): With an International Comparison for1905’, Rivista di Storia Economics: International Issue, 1, 1984.

53. Calculated from Zamagni, ‘An International Comparison’, p. 116, Table 5.1; and Table 5.7.54. H.A.W., ‘Capital and Labour’, in R. Lloyd, ed., Twentieth Century Impressions of Argentina,

London, p. 158-65. This guide was intended for businessmen, so its description of the cost ofliving was not intended to elicit sympathy for Argentina’s working classes.

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trouble have likewise had a share in raising the price of this commodity. [...] Sugaris dear and not over good, while tea, coffee, and cocoa being imported are naturallyhigh-priced by reason of the heavy Customs duties they have to bear, a remark thatapplies to all articles of food coming from abroad. Clothes are extremely expensive,a suit for which three and a half to four guineas [that is, around £4] would be paid inLondon costing $100 paper (or just on £9) in Buenos Aires. Lower prices than thiscan be paid, and it may be said a suit of clothes can be got from $45 paper (about £4upwards), but of the quality of the cheaper kinds, the less said the better, and herealso the worker suffers because he pays high and gets very poor value for money.And so with all articles of clothing for men and women alike. If made of importedmaterials the cost is exorbitant; if of stuffs manufactured in Argentina, then qualityis poor, and the life is short, and the initial cost is big.55

Even more than the prices of consumer goods, rents were believed to be

exorbitant in Buenos Aires. Indeed, there was a widespread tenant strike against the

high rents in 1907.56 A report of the National Labour Department published five years

later nonetheless found that rents were far higher in Buenos Aires than in Northern

Europe:

Rent in the Federal Capital is far higher than in other parts of the world and weighsfar more heavily on the tenant than in the European countries and more than in theNorth American cities. [...]

In Buenos Aires the monthly rent of the cheapest room [...] is, as a minimum,15.00 pesos, reaching prices of 30, 35, 45 and 50 pesos (for a room), with themonthly average being 28.00 pesos. The monthly rent of a single room in Paris costs3.70 pesos, and rooms of this type [...] are always abundant. Two-room housing canbe got for 5.50 pesos monthly, with an average of 6.50 pesos; those of three rooms,from 8 pesos per month, with an average of 10 pesos; and finally, those of fourrooms cost from 11.00 pesos and above.

In England, where housing of just one room has almost disappeared, [...] themonthly rent of this type of accommodation oscillates between 3 and 4 pesos permonth. Two-room accommodation costs 7 to 8 pesos monthly; three room, 9 to11.50 pesos; and four-room or more from 12 to 13.50 and above, but not goingbeyond 15 to 16 pesos. [...]

The current prices of renting two rooms [in Buenos Aires] are 40 pesos andabove; for three rooms, 60 and above; for four, 80 pesos and above; and these arenot in central neighbourhoods, but in the peripheries; the houses without services ofrunning water and drains, not having, moreover, in these neighbourhoods [...] anytype of convenient travel to and from the places of work. This is why we see somany staying in the central neighbourhoods, living in the uncomfortable and insanit-ary conventillos [workers’ boarding houses]. It is four or five times more expensiveto live in Buenos Aires than in London or Paris. And there are almost no conveni-ences in the houses, whereas there are many and dangerous inconveniences, bothmoral and hygienic.57

A lack of skilled labour and high tariff barriers for many goods were cited as

55. Ibid., p. 162.56. See J.A. Baer, ‘Tenant Mobilization and the 1907 Rent Strike in Buenos Aires’, Americas, 49:3,

1993.57. DNT, Boletín, 21, Buenos Aires, 1912, p. 427-28, author’s translation, emphasis added.

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the principle causes of the high cost of living. In the case of housing, Alejandro

Bunge, the prominent government statistician, argued that the exorbitant cost of

construction was due to the low productivity of Argentine construction workers,

which resulted from their ‘deficient schooling and professional education’.58 In an

account of a visit to Buenos Aires by a North American colleague, Bunge provided a

useful illustration of the consequences of this lack of training:

[S]howing Buenos Aires City to Mr William W. Davies, we stopped by a building inconstruction. Davies started to examine the labourers’ work, asking me what wasgoing on at the site. I responded that I could not see anything abnormal, but then Istarted to understand his question. It seemed to him that all the workers were ill, asif possessed by a species of flu that stopped them from walking, making use of theirsight, of their own will and their hands. Apart from the useless movements, the inde-cision and the listlessness that he noted, for him, the overall impression was of acinemagraphic film that the operator had slowed down to half the normal speed.59

On top of this low level of labour productivity, most construction materials also had

to be imported, then pay considerable taxes upon their arrival in Buenos Aires, which

drove up construction costs. In the terms of Juan B. Justo, the Socialist deputy for

Buenos Aires, ‘the enormous price increases that the Argentine tariff law imposes on

imported construction materials [...] is the principal cause of the high rents in this

city and all the country’.60 As Justo and other socialists often observed,61 high duties

moreover allowed politically connected industrialists to produce basic goods for sale

at high prices, thereby helping to drive up the cost of living in Buenos Aires.62

To quantify these contemporary impressions of Buenos Aires, it is necessary

to investigate the historical price record. In doing so, care must be taken because

small errors can have major effects. Williamson, for example, appears to have unwit-

58. A. Bunge, speech given to the Instituto Popular de Conferencias on 2 July 1920, reproduced inidem, Una nueva argentina, p. 386, fn. 7.

59. Ibid., p. 385.60. Justo, Obra parliamentaria, p. 51, author’s translation.61. For example, ibid., pp. 51-53.62. For consumer goods industries, rates of effective protection could be very high. Beer manufactur-

ers, for instance, were paying a tariff rate of approximately five percent on imports of hops and12 percent on malt, then sold their produce at prices that reflected an approximately 70 percenttariff rate on bottled beer and 80 percent on beer in casks; petroleum refiners could import crudepetroleum duty free, then turn it into paraffin, selling it locally at prices inflated by a 95 percenttariff rate; paper paste could be imported at five percent, then turned into wrapping paper or play-ing cards, both of which were protected by roughly 100 percent tariffs. These tariff rates wereestimated as tariffs collected divided by the tariff value of the imports in 1913. From DGEN, Elcomercio exterior argentino, n.d., pp. 163-64, 166, 175, 182, 184-85, Lines 122, 140, 228, 229,498, 502, 664, 711, and 739. Also see Pineda, Industrial Development, ch. 5.

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tingly used wholesale prices for Argentina, but retail prices for everywhere else, in

this way introducing a major downward bias into his estimates of the cost of living in

Argentina.63 As such, he has significantly overestimated the country’s PPP wages. If,

for instance, the wholesale prices used by Williamson are raised by 20 percent to

better reflect retail prices, it means that his estimate of PPP wages falls from 88

percent to 75 percent of the British level in 1909-11. Care must therefore be taken

when assessing price levels. For this reason, Appendix 5.1 will detail exactly where

the prices used here come from and how they have been processed to make them

comparable. The results can be seen in Table 5.8. They confirm that the cost of living

was high in Buenos Aires compared to the other cities, with the important exception

of the price of beef. Hence, beef in Buenos Aires cost perhaps just a third of the price

in London, but potatoes, paraffin, and rent were all three to four times as much.64 The

question then becomes to aggregate the prices of these goods to arrive at a single

price level for each place.

There are two main methodologies that have been used to assess aggregate

price levels. One uses a multilateral basket to weight the various prices, which can

then be used to calculate PPP wages, as in Williamson.65 The alternative consists of

calculating the cost of a basic basket that contains enough goods to secure the subs-

istence of a worker and his family, which can then be used to calculate welfare ratios,

as in Allen.66 Both methodologies, as was seen in Table 5.6, have been used to make

wages internationally comparable. Generally, historians have elected to use either

one or the other, which is problematic because, as Table 5.9 reveals, the different

methodologies can produce quite different outcomes. The price levels shown in Table

63. Williamson took his data indirectly from Bunge’s cost of living estimates, as reproduced byErnesto Tornquist, who did not mention that Bunge had used wholesale prices as proxies forretail prices. See Bunge, Intercambio económico, pp. 158-67; Tornquist, Economic Development,pp. 267-69; and Williamson, ‘Evolution of Global Labor’, p. 187. A similar problem afflictsCortés Conde’s widely used cost-of-living index. Cortés Conde inexplicably decided it was validto use retail beef prices for 1880-1901, then wholesale prices for 1902-12. Cortés Conde,Progreso argentino, p. 286, Cuadro 10. The result is to introduce a downward bias in the trend ofhis cost-of-living index, which then gives an upward bias to the trend of his ‘real’ wage series.

64. Efforts were made to underestimate the cost of living in Buenos Aires, particularly with regard tothe price of beef and rents. Most likely, both are too low for Buenos Aires in Table 5.8 becausethey refer to cuts of meat and types of housing that were inferior to those in the other cities. Alsosee Appendix 5.1, page 226.

65. Williamson, ‘Evolution of Global Labor’, pp. 177-94.66. Allen, ‘Great Divergence’; Allen et al, ‘Wages, Prices’; and Allen, Murphy, and Schneider,

‘Colonial Origins’.

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Table 5.8International Prices, c. 1905-09

BuenosAires

(1907)

Berlin(1905)

London(1905)

Paris(1905)

Montreal(1905)

NewYork

(1909)

Sydney(1907)

Beef (d per kg) 5 18 15 19 13 13 8Bread (d per kg) 4.6 3.0 2.6 3.3 5.8 5.9 3.4Milk (d per lt) 2.5 2.3 3.5 2.4 3.5 3.1 3.8Potatoes (d per kg) 3.1 0.7 1.0 1.2 0.9 2.6 1.1Sugar (d per kg) 7.3 5.9 4.7 6.1 5.4 6.1 5.5Wheat flour (d per kg) 3.1 5.0 3.0 3.9 3.5 3.9 2.8Paraffin (d per lt) 5.2 2.4 1.6 2.3 2.7 1.6 2.4Rent (3 rooms, s per week) 25 7 7 6 7 12 9

Note: The prices are in British currency. There were 12 pennies (d) per shilling (s), and 20shillings per pound (£). For the raw data and details of how the prices were processed, seeAppendix 5.1.

Sources:

Buenos Aires: DNT, Boletín, 3, p. 345; and Cortés Conde, Progreso argentino, p. 290, Cuadro12.

Berlin: Board of Trade, Cost of Living in German Towns, pp. 28, 35, 37.

London: idem, Cost of Living of the Working Classes, pp. 12, 16-18.

Paris: idem, Cost of Living in French Towns, pp. 22, 30, 33.

Montreal: Board of Inquiry, Cost of Living, I, pp. 167, 475.

New York: Board of Trade, Cost of Living in American Towns, pp. 39, 46-47.

Sydney: New South Wales, Statistical Register for 1919-20: Part VIII: Social Conditions,Sydney, 1921, pp. 411, 413.

Gold standard exchange rates from Tornquist, Economic Development, p. 328.

5.9 come from applying the two methodologies to the prices in Table 5.8. Both meth-

odologies find that Buenos Aires was the second most expensive city in the sample,

after New York. However, whereas the multilateral basket indicates that the price

level in Buenos Aires was 16 percent higher than in London, the subsistence basket

suggests that it was 71 percent higher.

The price level used will affect the assessment of income levels. In Table 5.10

this can be seen in the results of applying these different price levels to the nominal

weekly wages in Table 5.7. According to the PPP wages calculated using the multi-

lateral-basket price level, the wages of unskilled construction labourers in Buenos

Aires were at around the same level as in Berlin and Paris, which was 75 to 85

percent of the level in London. The welfare ratios calculated using the subsistence

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Table 5.9International Price Levels, c. 1905-09

London = 100Basket type: Multilateral* Subsistence**

Buenos Aires (1907) 114 171Northern Europe

Berlin (1905) 107 91London (1905) 100 100Paris (1905) 112 103

European offshootsMontreal (1905) 119 127New York (1909) 135 173Sydney (1907) 96 112

* Calculated as the geometric mean of the prices in Table 5.8, weighted according to theiraverage share in expenditure on the goods in the seven cities.

** Calculated as the cost of a basic basket of goods including enough food to providesufficient calories for the subsistence of a man, woman, and two children for a week, 100millilitres of paraffin, and one third of the weekly rent of a three-room flat. The compositionof the food baskets is varied according to the prices of food in each city.

Sources: See Appendix 5.1.

baskets, by contrast, indicate that workers’ incomes were inferior to those in all the

other cities: they were around 54 percent of the level of London, whereas in Berlin

incomes were 96 percent of the London level, and in Paris, 83 percent. For the

skilled workers, similarly, their PPP wages in Buenos Aires appear higher than in

Berlin or Paris, but their welfare ratios are lower. The two methodologies thus lead to

different conclusions: according to the PPP wages, incomes in Buenos Aires were at

least equivalent to incomes in Northern Europe, but the welfare ratios show them as

being considerably lower. A problem with the existing literature, then, is that it has

failed to recognise how the two methodologies can produce quite different results.

To understand why these differences occur, it is necessary to consider the two

methodologies further. The PPP wages, as pioneered by Williamson and followed

here, are calculated on the assumption that workers would have substituted cheaper

goods for more expensive goods within the multilateral basket. They assume, for

instance, that a worker in Buenos Aires would have chosen to spend less on housing

and more on meat because the former was relatively expensive, while the latter was

relatively cheap. The price level is therefore calculated as a weighted geometric

mean of the various individual prices in the multilateral basket, which, in mathemat-

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Table 5.10International Wage Levels in Construction, c. 1905-09

PPPwages*

Welfareratios**

PPPwages*

Welfareratios**

s per week 1 = subsistence London = 100

(a) Unskilled construction workers

Buenos Aires (1907) 23-25 1.7-1.8 78-84 52-56Northern Europe

Berlin (1905) 24 3.9 81 96London (1905) 30 4.6 100 100Paris (1905) 22 3.7 74 83

European offshootsMontreal (1905) 35 4.8 118 113New York (1909) 52 5.9 172 138Sydney (1907) 45 5.2 149 129

(b) Skilled construction workersBuenos Aires (1907) 41-50 3.0-3.6 92-111 62-75Northern Europe

Berlin (1905) 31-37 4.9-6.0 69-83 81-98London (1905) 45 6.9 100 100Paris (1905) 35-39 5.7-6.4 77-87 86-97

European offshootsMontreal (1905) 52-86 7.1-11.6 116-91 111-82New York (1909) 69-86 7.9-9.8 154-92 124-54Sydney (1907) 59-70 6.9-8.1 132-55 114-34

* Nominal wages from Table 5.7 deflated by the multilateral price level in Table 5.15.

** Nominal wages from Table 5.7 divided by the cost of the baskets underlying thesubsistence price level in Table 5.9.

Source: Tables 5.7 and 5.9.

ical terms, replicates the effect of such substitutions. The subsistence baskets used to

calculate the welfare ratios are, on the other hand, fixed: they assume that no substi-

tution was possible since they are intended as a measure of how far people were from

the ‘line between respectability and destitution’.67 For people on low incomes, it is

unrealistic to assume that they can substitute one thing for another, given that they

are attempting to attain the bare minimum of everything, which is reflected in the

composition of the subsistence baskets. Hence, whereas the PPP wages are an essen-

tially theoretical measure of what people’s incomes could have been, had they

switched their expenditure between different types of goods and services, the welfare

67. Allen, ‘Great Divergence’, p. 426.

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ratios give a much more concrete indication of what they actually were.68

These methodological considerations help make sense of the international

comparisons made so far. In theory, the purchasing power of wages in Buenos Aires

was comparable to the leading cities of Northern Europe, as shown by the high PPP

wages in Table 5.10. Moreover, substitution did take place in practice. Specifically,

people in Buenos Aires appear to have consumed vast quantities of meat, while

living in very humble housing. Probably well over 100 kilos of meat per inhabitant

were consumed annually in the city,69 which was higher than in Australia, where

around 70 kilos were consumed per person,70 or the 60 kilos per capita consumed in

Britain.71 Such heavy meat consumption was rational because meat was very cheap:

incredibly, in Buenos Aires beef was a cheaper way to obtain calories than potatoes.72

On the other hand, surveys conducted by the National Labour Department prior to

the First World War found that 80 percent of working-class families lived in just one

room,73 whereas in the cities of the more developed countries they enjoyed far more

spacious accommodation: in New York flats of three to five rooms were the norm;74

in all the Northern European cities over half of working-class families lived in at

least three rooms;75 indeed, even in Milan the majority of families had at least two

68. Unfortunately, these issues are rarely discussed in the existing literature, with historians too oftenneglecting to explain why they have chosen one methodology over another, instead preferring topresent their numbers as faits accomplis. Williamson, for example, simply states that he uses‘Cobb-Douglas indices throughout’ (‘Evolution of Global Labor’, p. 188), without explainingwhy or even what that means. (It translates as an index calculated as the ‘weighted geometricaverage of price relatives’. B.M. Balk, Price and Quantity Index Numbers Models for MeasuringAggregate Change and Difference, Cambridge, 2008, p. 228.) To understand the significance ofthis, it is necessary to look closely at debates in the technical literature, particularly thosesurrounding the use of arithmetic and geometric means to calculate contemporary price indices.See, for example, K.V. Dalton, J.S. Greenlees, and K.J. Stewart, ‘Incorporating a GeometricMean Formula into the CPI’, Monthly Labor Review, October 1998; M. Ward, D. Blades, and C.Carson, ‘How Relevant are the United Kingdom’s Official Measures of Price Change?’, Statist-ical Journal of the IAOS, 27:1-2, 2011; and ABS, A Guide to the Consumer Price Index: 16thSeries, Canberra, 2012, ch. 4.

69. A contemporary estimate put the city’s meat consumption at 117 kilos per person in 1906. J.B.González, El encarecimiento de la vida en la República Argentina, Buenos Aires, 1908, p. 89.

70. Meat consumption from BCS, Trade Unionism, Unemployment, Wages, Prices, and Cost ofLiving in Australia, 1891-1912, Melbourne, 1912, p. 47. Population from Maddison, WorldEconomy, II, p. 460, Table 2a.

71. Royal Society, ‘The Food Supply of the United Kingdom’, Parliamentary Papers, Cd. 8421,1916, pp. 3, 10, Table 1.

72. Obtaining 1,000 calories from beef cost around two pennies; from potatoes, around four. SeeAppendix 5.1, page 230, Table A5.6.

73. Bunge, Nueva Argentina, p. 266. Families also tended to be large in Argentina, as indicated bythe high dependency rate. Taylor, ‘External Dependence’, p. 916, Figure 2.

74. Board of Trade, Cost of Living in American Towns, p. 38.75. Board of Trade, Cost of Living in German Towns, p. 18; and idem, Cost of Living in French

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rooms.76 The relative prices prevalent in Buenos Aires thus meant that people ate

more meat than in the cities of the world’s most developed countries, while living in

housing that was most likely worse than the cities of the Southern European peri-

phery. Such possibilities for substitution led to the high PPP wages seen in Table

5.10.

Yet substitution had its limits, resulting in the far less optimistic picture

painted by the welfare ratios. For an unskilled male worker in Buenos Aires, accord-

ing to the welfare ratios calculated here, his wages were less than twice the cost of

securing subsistence for his family, whereas in the other cities they were four to six

times the subsistence level. In theory, then, workers in Buenos Aires, thanks to the

possibilities for substituting different types of goods and services, could enjoy wages

that were the same as those received by workers in some of the major cities of North-

ern Europe, but in practice they were far closer to destitution than their Northern

European counterparts. Crucially, some goods and services were not substitutable

because workers had to secure at least the minimum of everything, which, as the

welfare ratios in Table 5.10 indicate, was far more difficult in Buenos Aires than in

the other cities. Welfare ratios therefore give a more accurate measure of actual

incomes than the Williamson-style PPP wages, assuming that these welfare ratios can

be generalised from the major cities to the countries as a whole.77 They suggest that

Argentines probably did not enjoy incomes at the same level as Northern Europeans,

let alone the inhabitants of the European offshoots.78

Paradise Lost?This chapter has assessed the frequently repeated claim that Argentina was once ‘one

of the richest countries in the world’. By comparing Argentina’s living standards at

the beginning of the twentieth century with those of the world’s most developed

countries, it has found that Argentina failed to reach their heights. Building on the

Towns, p. 16. 76. Società umanitaria, Le condizioni generali della classe operaia in Milano: Salari, giornate di

lavoro, reddito, ecc., Milan, 1907, p. 54.77. In the case of Argentina, contemporary observations suggest that workers’ ‘real’ incomes were

lower outside Buenos Aires City. Most famously, this was suggested in a major qualitative reporton living standards in Argentina, published as J. Bialet Massé, Informe sobre el estado de lasclases obreras argentinas, I and II, La Plata, (1904) 2010.

78. For other measures of the price level that reinforce this more pessimistic conclusion, seeAppendix 5.1, especially page 233, Table A5.7.

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pessimistic revision of Argentina’s long nineteenth century made in Chapter 4, the

chapter has argued that the root of Argentina’s failure was an oligarchic state that

could not be democratised because the losers from Argentina’s terms-of-trade had to

be excluded from politics. The provision of public goods was limited as a result,

leading to the low levels of public welfare, especially outside the capital city. A lack

of education resulted in a shortage of skilled workers, which, combined with the high

tariffs obtained by some politically-connected industrialists, drove up the prices of

many manufactured goods due to low levels of labour productivity. Evaluating

exactly how high the price level was depends upon the methodology used and, inev-

itably, more debates could be had about which is most appropriate. Here it has at

least been demonstrated that such debates are necessary. It has also been argued that

the subsistence-basket price level gives the best indication of the cost of living,

suggesting that wage levels in Buenos Aires also trailed those of Northern Europe

and the European offshoots.

This chapter has, then, verified the pessimistic revision of Argentina’s long

nineteenth century. Despite the kind of claims that are often made about its ‘golden

age’, Argentina was not one of the world’s most developed countries prior to the First

World War, as its levels of human development were below those attained in North-

ern Europe and the European offshoots. From this perspective, there has been no

‘Argentine paradox’, as there was no paradise to lose. As Chapter 6 will argue, the

implication of this finding is that much of the historiography of the country’s twenti-

eth century must also be revised.

Appendix 5.1: International Price Levels, c. 1905-07This appendix details the origins and processing of the price data used to assess

national incomes in this chapter. The principal purpose, as in some previous appen-

dices of this dissertation, is to facilitate reproducibility through full disclosure of

where the data have come from and what has been done to them to arrive at the

results described above. All of the data have already been presented in their

processed form in Table 5.8, while in Table A5.1 they are presented in an almost raw

form, with the only processing done being to convert the prices for Buenos Aires and

Montreal to sterling using the gold standard exchange rates,79 and to convert the

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prices for food and paraffin in all the cities to the metric system.80 The remainder of

the appendix will discuss how these prices were further processed and turned into the

price levels presented in Table 5.9. The appendix begins by discussing the processing

of the food prices, then it discusses the figures for rents; finally, it outlines how the

multilateral-basket and subsistence-basket price levels were calculated, as well as

presenting some other price levels that are based on alternative baskets.

Food PricesThe processing of food prices was relatively simple, except for the case of beef.

When a range of prices was given in the source the average of the two extremes was

used. In London, for instance, the price of bread was reported as ranging from 2.2 to

three d per kilo, so the price was taken to be 2.6 d. This produced single prices for

most goods in every city.

Calculating beef prices was more complicated because, as shown in Table

A5.1, the sources gave a range of prices for different cuts. A single meat price was

arrived at for each place by amalgamating the prices of the middling cuts, as follows:

1) Buenos Aires: the price for the generic ‘carne’ was deduced to represent a cut

resembling silverside (carnaza), which it appears to have been equivalent to,

according to later price data in which both ‘carne’ and various other cuts are

given.81

2) Berlin: the geometric mean of ribs, flank, silverside, and shin without bone.

3) London: the geometric mean of ribs, thick flank, silverside, and shin without

bone.

4) Montreal: medium chuck.

5) New York: the geometric mean of flank, roasts (ribs second cut), roasts

(chuck or short ribs), and shin without bone.

6) Paris: the geometric mean of ribs, thick flank, silverside, and shin without

79. Gold standard exchange rates were used because these appear to have been exchange rates usedto convert prices to sterling in the other cities. All these countries were on the gold standard at thetime.

80. The metric system was used simply because it is less complicated than imperial weights andmeasures.

81. See C. Llorons do Azar, ‘Precios unitarios de artículos de consumo y servicios, Capital Federal yprovincias: 1901-1963: Parte Primera’, mimeo, n.d., p. 6.

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Table A5.1International Prices (Raw), c. 1905-09Buenos

Aires(1907)

Berlin(1905)

London(1905)

Montreal(1905)

New York(1909)

Paris(1905)

Sydney(1907)

Beef (d per kg)Generic 5Chops (leg) 8Chops (loin) 9Chops (neck) 7Corned beef 9Flank (generic) 14-17 11Flank (thick) 10-22 27Flank (thin) 4-14Gravy beef 7Medium chuck 11-14Plate brisket (fresh) 11 12Plate brisket (preserved) 8Ribs 17-19 10-23 23 9Roasts (chuck ribs) 13Roasts (ribs, 1st) 18Roasts (ribs, 2nd) 15Roasts (round) 18Shin, without bone 17 9-18 12 15Shin, with bone 14 8-13 12Silverside 19-24 10-20 17Sirloin 11Steak 24-27Steak (beef) 11-24Steak (round) 20Steak (rump) 18-31 30 16Steak (shoulder) 8Steak (sirloin) 8-24 21

Bread (d per kg)Generic 2.2-3.0 5.8 5.9 3.3 3.42nd class 4.6Black 2.6Grey 3.0

Flour (wheat) (d per kg) 3.1 5.0 2.5-3.5 3.5 3.9 3.9 2.8Milk (d per lt) 2.5 2.2-2.4 3.5 3.5 3.1 2.4 3.8Potatoes (d per kg) 3.1 0.6-0.7 0.9-1.1 0.9 2.6 1.2 1.1Sugar (d per kg)

Generic 5.5Demerara 4.4-5.5Loaf 6.1 5.0-5.5 6.1Tucumán 2nd 7.3White granulated 5.5-6.1 4.4 5.4 6.1

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Table A5.1 (cont.)Buenos

Aires(1907)

Berlin(1905)

London(1905)

Montreal(1905)

New York(1909)

Paris(1905)

Sydney(1907)

Sugar (d per kg, cont.)Yellow 4.4 5.4

Paraffin (d per lt) 5.2 2.4 1.3-1.8 2.4-2.9 1.6 2.3 2.4Rents (s. per week)

1 room 9-112 room 2-6 3-63 room 5-9 5-9 9-14 4-7 94 room 6-10 12-17 5-8 125 room 7-12 14-25 156 room 9-13 12-15 177 room 19

Note: The prices are in British currency. There were 12 pennies (d) per shilling (s), and 20shillings per pound (£). All prices from the original sources were converted to pounds sterlingand metric measures.

Sources:

Buenos Aires: Cortés Conde, Progreso argentino, p. 290, Cuadro 12.

Berlin: Board of Trade, Cost of Living in German Towns, pp. 28, 35, 37.

London: idem, Cost of Living of the Working Classes, pp. 12, 16-18.

Paris: idem, Cost of Living in French Towns, pp. 22, 30, 33.

Montreal: Board of Inquiry, Cost of Living, I, pp. 167, 475.

New York: Board of Trade, Cost of Living in American Towns, pp. 39, 46-47.

Sydney: New South Wales, Statistical Register for 1919-20: Part VIII: Social Conditions,Sydney, 1921, pp. 411, 413.

Gold standard exchange rates: Tornquist, The Economic Development, p. 328.

bone.

7) Sydney: the geometric mean of ribs, gravy beef, steak (shoulder), and three

chops (loin, leg, and neck).

Given this processing, it must be remembered that the beef price presented in Table

5.8 is approximate. Other than this, the only processing used was to take the geomet-

ric mean of sugar prices for each city (when multiple sugar prices were given).

Finally, grey rather than black bread was used for Berlin.

RentsMore consideration must be given to rents because they weighed heavily in the cost

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Table A5.2Cortés Conde’s Rent Series, 1903-12

m$n per month s per week1903 14.90-17.50 5.9-6.91904 15.47-17.50 6.11905 19.50 7.71906 19.50 7.71907 21.69-27.50 8.6-10.81910 29.49 11.61912 29.56 11.7

Note: The figures show the rent of a single room in Buenos Aires. The rents were convertedinto sterling at the gold standard rate of 11.45 paper pesos (m$n) per £.

of living in Buenos Aires. For that city, the figure presented in Table A5.1 comes

from Roberto Cortés Conde’s compilation of rents, which he used to calculate a cost

of living index. His rents for a single room for the years 1903-12 are reproduced in

Table A5.2. For 1907, the year in question, his low figure comes from a survey by

Argentina’s National Labour Department (DNT) of 23 conventillos (poor workers’

boarding houses) whose tenants went on strike in that year.82 The findings of that

survey are reproduced in Table A5.3. The higher figure, meanwhile, comes from a

contemporary study by Juan González in which he stated that the ‘price of housing

was, on average, 25 to 30 pesos [per month]’ in 1907.83 In order not to bias the figure

for Buenos Aires’ cost of living upward, the lower DNT figure was used. As can be

seen in Table A5.3, it was for the average rent paid for the 3,146 rooms in the 23

conventillos, so it was possible to pay lower rents in Buenos Aires. However, it

would not be appropriate to compare the lowest possible rent in Buenos Aires with

the figures for the other cities, as those appear to be average rents. On the other hand,

nor were the rents in the other cities for the cheapest form of housing, whereas

conventillos were around the cheapest type in Buenos Aires – as a result, these

figures probably underestimate equivalent rents in that city.

To make rents in all the cities comparable, it was necessary to arrive at an

approximate figure for housing with the same number of rooms. As the sources for

five out of seven cities gave rents for three-room housing, this number was used.

Buenos Aires and Montreal presented problems because the sources only gave

82. Again, see Baer, ‘Tenant Mobilization’; on this survey, see p. 356.83. González, Encarecimiento de la vida, p. 50, author’s translation.

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Table A5.3Rents in 23 Conventillos in Buenos Aires, 1907

Conventillo Number ofrooms

Number ofpersons

Average roomsper person

Average rent per roomm$n per month s per week

1 51 300 6 27.50 10.82 13 48 4 33.50 13.23 15 35 2 22.00 8.74 20 90 5 25.00 9.95 17 35 2 26.00 10.36 17 60 4 28.00 11.07 43 350 8 21.00 8.38 22 65 3 21.00 8.39 13 43 3 19.50 7.7

10 42 150 4 20.00 7.911 48 160 3 18.00 7.112 6 11 2 16.50 6.513 32 125 4 20.50 8.114 49 220 4 21.00 8.315 12 20 2 20.00 7.916 130 700 5 22.45 8.917 24 102 4 19.00 7.518 20 60 3 24.50 9.719 9 41 5 20.00 7.920 15 58 4 18.00 7.121 19 80 4 14.80 5.822 56 250 4 17.70 7.023 35 143 4 23.00 9.1

Average: 708 3,146 4 21.69 8.6

Note: The rents were converted into sterling at the gold standard rate of 11.45 paper pesos(m$n) per £.

Source: DNT, Boletín, 15, Buenos Aires, 1910, p. 853.

figures for one- and six-room housing respectively. For Buenos Aires, the one-room

rent was converted to a three-room rent using the ratios from another DNT survey for

1914, as reproduced by Alejandro Bunge. Shown in Table A5.4, the DNT found that

the average rent of three rooms in 1914 was 2.8 times the rent of a single room, so

that ratio was applied to the rent of a single room in 1907 (8.6 s per week) to estimate

the rent of three rooms (24 s per week) in that year. In the case of Montreal, by

contrast, the rent of six rooms was simply halved. While somewhat crude, this

procedure would have, for instance, arrived at an accurate three-room rent for

Sydney.

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Table A5.4Rents in Buenos Aires, 1914

Number of rooms m$n per month s per week1 19.6 82 36 143 54 214 72 285 90 35

Note: The rents were converted into sterling at the gold standard rate of 11.45 paper pesos(m$n) per £.

Source: Bunge, Renta y riqueza, p. 267.

The Price LevelsIn the chapter the procedure used to calculate the multilateral-basket and subsistence-

basket price levels has already been briefly described. To elaborate further, they were

calculated in this way:

1) The multilateral-basket price level, following Williamson’s lead, was calcu-

lated using the geometric mean of the price relatives of the five items of food,

as well as those of paraffin and rent. To determine the weight assigned to each

food item, contemporary reports of consumption patterns in the various coun-

tries were used to roughly estimate the quantity of each item consumed in the

cities. Those quantities were then multiplied by the prices of the goods in

each city, which then gave the expenditure shares shown in Table A5.5. The

average of the share across the seven cities was then used to weight the five

items in the food element of the multilateral basket. With the overall price

level, food was then assigned a weight of 0.8, paraffin 0.05, and rent 0.15 –

weights that were somewhat arbitrarily assigned based on the expenditure

surveys reported by Williamson.84

2) The subsistence-basket price level was calculated as the weekly cost of a bas-

ket of food sufficient to provide around 5,825 calories per day, as well as 100

ml of paraffin, and a third of the weekly rent of three rooms,85 which would

84. Williamson assigns food 0.82 and rent 0.18. Williamson, ‘Evolution of Global Labor’, p. 185,Table A3.2.

85. This is an artificial measure of minimum rents, but it was necessary because of the lack of data

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Table A5.5Expenditure Shares on Five Food Items

BuenosAires Berlin London Paris Montreal New York Sydney Average

Meat 0.25 0.31 0.41 0.43 0.35 0.39 0.37 0.36Bread 0.43 0.34 0.24 0.36 0.24 0.14 0.20 0.28Milk 0.12 0.17 0.18 0.09 0.15 0.12 0.17 0.14Potatoes 0.10 0.08 0.07 0.07 0.08 0.15 0.06 0.09Sugar 0.10 0.05 0.10 0.04 0.09 0.09 0.16 0.09Wheat flour 0.01 0.05 0.00 0.00 0.10 0.11 0.05 0.04Total 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Sources:

Physical consumption levels:

Buenos Aires: Tornquist, Economic Development, p. 273.

Berlin: Board of Trade, Cost of Living in German Towns, pp. xxvii.

London: Board of Trade, Cost of Living of the Working Classes, pp. xxviii.

Montreal: Board of Inquiry, Cost of Living, I, p. 137.

New York: Board of Trade, Cost of Living in American Towns, pp. xxxiii.

Paris: Board of Trade, Cost of Living in French Towns, p. xxiv.

Sydney: Bureau of Census and Statistics, Trade Unionism, p. 47.

To arrive at expenditure, the physical consumption levels reported in these sources weremultiplied by the prices in Table 5.8.

have provided a subsistence-level standard of living for a small family. The

content of the food basket was different for each city, based on the costs of at-

taining calories for each item.86 The first step was to identify how much it

cost to obtain 1,000 calories from each food item, as shown in Panel (a) of

Table A5.6. The food baskets were then constructed for each city based on a

subjective evaluation of the costs of obtaining calories. In Panel (b) it can be

seen that this meant, for example, that there was only a small quantity of

potatoes and sugar in the Buenos Aires basket because these were an expens-

ive way to obtain calories, whereas there was far more in London, given that

these items were a relatively cheaper way to obtain calories there.

As shown in this chapter, these two methods of calculating the price levels

on the rent of just one room in all the cities except Buenos Aires.86. No wheat flour was included in the subsistence basket because wheat flour tended to be bought

by better-paid workers who had the means to turn it into bread at home. It would, consequently,be inappropriate to include it in a subsistence (that is, a poor person’s) basket.

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Table A5.6Cost of Calories and Food Baskets

BuenosAires Berlin London Paris Montreal New York Sydney

(a) d per 1,000 calories*Beef (1,800 cal per kg) 2.8 9.9 8.4 10.6 6.9 7.0 4.4Bread (2,700 cal per kg) 1.7 1.1 1.0 1.2 2.1 2.2 1.3Milk (600 cal per lt) 4.2 3.8 5.8 4.0 5.8 5.2 6.3Potatoes (700 cal per kg) 4.4 0.9 1.4 1.7 1.3 3.7 1.6Sugar (3,900 cal per kg) 1.9 1.5 1.2 1.6 1.4 1.6 1.4

(b) Weekly subsistence baskets**Beef (kg) 4.6 1.4 2.4 2.2 3.6 5.3 4.6Bread (kg) 9.5 9.3 8.0 10.5 5.5 3.9 5.6Milk (lt) 4.2 6.0 4.5 3.6 5.4 6.4 4.5Potatoes (kg) 2.8 9.7 6.2 5.7 10.9 10.1 5.4Sugar (kg) 0.6 0.7 2.0 0.6 2.2 2.5 2.8

Total calories: 5,821 5,821 5,823 5,829 5,826 5,819 5,829

* Calculated by the dividing the price of the goods in Table 5.8 by the calorific content ofeach good, then multiplying by 1,000.

** Quantity of the good in each city’s basket.

Sources:

Calorific content: based on US Department of Agriculture (USDA), ‘National NutrientDatabase’, available online at http://ndb.nal.usda.gov (accessed 3 May 2012).

Prices: Table 5.8.

produce quite different results, with the subsistence basket indicating a considerably

higher cost of living for Buenos Aires. To check the results, therefore, the price levels

were also calculated using four other types of basket, as follows:

3) The arithmetic multilateral-basket price level uses the arithmetic mean rather

than the geometric mean to weight the items in the multilateral basket. This

assumes, then, that consumers do not or cannot substitute cheaper goods for

more expensive goods.87

4) The mixed multilateral-basket price level assumes that substitution can only

take place within elements of the multilateral basket, but not between them.

87. This is, for instance, the methodology used in the construction of the United States’ consumerprice index (CPI) today, as the Bureau of Labor Statistics only uses the geometric mean at themost basic level – a methodology replicated here when calculating beef and sugar prices. SeeDalton, Greenlees, and Stewart, ‘Incorporating a Geometric Mean’.

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Hence, the geometric mean is used to calculate the food price level, while the

arithmetic mean is applied to the food, rent, and paraffin elements to calculate

the overall price level.

5) The poverty basket price level is the cost of 15.1 kg of bread or 58.3 kg of

potatoes (depending upon which is the cheaper way to access calories in each

city), plus a third of the three-room rent. The poverty basket thus leads to a

price level that indicates how expensive it was to fulfil the most basic needs

of food and shelter for a small family, as the quantity of bread or potatoes in-

cluded would have been sufficient to provide around 5,825 calories per day

for a week.

6) The destitution basket price level is the cost of 15.1 kg of bread or 58.3 kg of

potatoes, without any rent. It accordingly replicates the cost of living for a

homeless family.

Panel (a) in Table A5.7 shows the price levels that result from these different

methodologies, while in Panel (b) they are applied to the wages of an unskilled

construction labourer in each city to arrive at ‘real’ wages. As was already seen in

this chapter, the Williamson-style (geometric) multilateral basket leads to price levels

that minimise the differences between the cities, whereas the subsistence basket

suggests they were far greater. When both are compared to the price levels calculated

using the other four types of basket, it can be seen that the Williamson-style price

level is the outlier – an impression that Table A5.8 confirms using correlation coeffi-

cients. Notably for the analysis presented in this chapter, none of the other price

levels, with the possible exception of the mixed multilateral basket, give the impres-

sion that labourers in Buenos Aires enjoyed living standards comparable to the

biggest cities of the world’s most developed countries.

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Table A5.7Alternative Estimates of the Price Levels(1) (2) (3) (4) (5) (6)

Multilateral(geometric) Subsistence Multilateral

(arithmetic)Multilateral

(mixed) Poverty Destitution

(a) Price level, London = 100Buenos Aires (1907) 113 160 161 137 246 177Northern Europe

Berlin (1905) 106 90 109 106 98 97London (1905) 100 100 100 100 100 100Paris (1905) 110 101 113 112 107 127

European offshootsMontreal (1905) 116 124 126 117 118 134New York (1909) 133 169 146 134 201 227Sydney (1907) 96 111 103 97 130 131

(b) ‘Real’ wages of an unskilled labourer, London = 100Buenos Aires (1907) 79-85 56-60 56-60 66-71 37-39 51-55Northern Europe

Berlin (1905) 82 96 79 81 88 90London (1905) 100 100 100 100 100 100Paris (1905) 76 83 74 75 78 66

European offshootsMontreal (1905) 120 113 111 120 118 105New York (1909) 175 138 160 174 116 103Sydney (1907) 150 129 140 147 110 110

Source:

Nominal wages: see Table 5.7.

Price levels: see the text.

Table A5.8Correlation Coefficients of Price-Level Estimates

Multilateral(geometric) Subsistence

(1) Multilateral (geometric) 0.76(2) Subsistence 0.76(3) Multilateral (arithmetic) 0.74 0.91(4) Multilateral (mixed) 0.84 0.89(5) Poverty 0.55 0.92(6) Destitution 0.83 0.95

Average: 0.74 0.89

Note: In the correlation coefficients, 1 equals perfect positive correlation, -1 perfect negativecorrelation.

Source: Calculated from Table A5.7

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Chapter 6

Conclusion

Nothing is built upon rock: for all is built upon sand:but let each man build as if sand were rock.

Jorge Luis Borges, ‘From an Apocryphal Gospel’1

This dissertation has provided a pessimistic revision of Argentina’s long nineteenth

century by interpreting it within the context of a new metanarrative of global diver-

gence. To recap, Chapter 1 introduced the dissertation by placing it within its histor-

iographical context; Chapter 2 demonstrated that during the long nineteenth century

the periphery experienced a terms-of-trade boom that was longer, greater, and more

widespread than has previously been supposed; Chapter 3 discussed how this long

boom drove global divergence by allowing land-abundant regions to prosper, while

making land-scarce regions stagnate; Chapter 4 described how Argentina’s own

terms-of-trade boom had the same effects within the country, as the Littoral

progressed at the same time as the interior declined, giving Argentina’s development

an unevenness that prevented it from fulfilling its potential as a land-abundant coun-

try; Chapter 5 then verified this pessimistic revision by showing that living standards

in Argentina at the beginning of the twentieth century were below those of the

world’s most developed countries, despite frequent claims that it was ‘one of the

richest countries in the world’.

The more optimistic vision, this dissertation has maintained, tends to over-

look the losers from Argentina’s long terms-of-trade boom. The relatively land-

scarce regions of the interior are largely absent from the optimistic historiography,

with the focus instead on the land-abundant Pampean zone.2 This leads to the false

1. In J.L. Borge, In Praise of Darkness, New York, 1974, p. 111.2. For example, Cortés Conde, Progreso argentino; idem, ‘Export Economy’; idem, ‘Growth of the

Argentine Economy’; idem, Economía argentina; and idem, ‘Vicissitudes of an Exporting

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impression that Argentina was a new ‘settler society’, whereas in reality it was not.

While the Pampas had been neglected under the Spanish empire, parts of the interior

were relatively densely populated, and they tended to lose out from the long boom

after independence. These regions saw their cottage industries undermined by

cheaper imports, as well as the rising cost of raw materials, but they lacked the land

resources that would have allowed them to take advantage of improved terms of

trade. Furthermore, the new industries that did emerge – sugar in the North and wine

in the West – created little permanent employment, and ethnic discrimination in the

Pampean zone restricted possibilities for internal migration. The interior therefore

declined, even as the Littoral progressed.

This dissertation has insisted on the importance of the losers to Argentina’s

development during the long nineteenth century. Crucially, it has argued, the inter-

ior’s stagnation would have a profound impact on the country’s institutions, as the

state was substantially built by politicians from the interior. Whereas the optimistic

interpretation of the National Autonomist Party (PAN) is that it used the federal

government to promote the interior’s development, particularly through the extension

of the railway network,3 this dissertation has contended that the PAN represented

those elements of the interior’s ruling classes that had been unable to obtain signific-

ant popular support within their provinces, so they required a strong federal govern-

ment to buttress their position against the discontent of their rural poor. This support

came when the railways augmented the national army’s capacity to operate across

Argentina, thereby allowing the federal government to intervene in favour of its

supporters. Moreover, the railways also provided the provincial ruling classes the

opportunity to profit from the long boom due to the falling costs of internal transport-

ation, which led to a convergence of interests between the ruling classes of the inter-

ior and the Littoral.

For Argentina’s development, the interior’s decline mattered principally

because it meant that the state formed by excluding much of the country’s popula-

tion – the interior’s peasantries – from politics. The resulting lack of accountability

ensured that public land was privatised in a manner that suited the great landowners,

Economy’.3. Llach, ‘Wealth of the Provinces’; and Gerchunoff, Rocchi, and Rossi, Desorden y progreso; cf.

Duncan, ‘Política fiscal’.

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while laws intended to encourage land redistribution were instead used by public

officials to appropriate land for themselves. The native born, moreover, had diffi-

culties accessing the land even as tenants due to the racism of Argentina’s ruling

class, which was reinforced by the positivist belief that progress would come by

improving the country’s racial stock. In this way, Argentina’s oligarchic state,

combined with its ruling ideology, restricted access to the land, thereby muting the

safety-valve effect of the expanding frontier. The floating population of landless

labourers grew as a result, which put downward pressure on wages, so there were

fewer incentives for capitalists to invest in the technologies that would have raised

labour productivity. For this reason, Argentina’s intensive growth was limited

compared to the European offshoots.

Argentina’s good fortune during the long nineteenth century was thus to

possess vast quantities of land, but its misfortune was to simultaneously have land-

scarce regions that lost out from improved terms of trade. Argentina differed from the

prosperous land-abundant European offshoots because it was already populated when

the long boom began. It was not, in other words, a ‘region of recent settlement’, as it

had inheritted a large peasant population from the Spanish empire. In Australasia and

North America, by contrast, the losers from the long boom – the indigenous

peoples – were few, so they could be more easily excluded (or exterminated) by

settlers. White egalitarianism, which became the ruling ideology of these new societ-

ies, then led to public policies that facilitated access to the land, with the US

Homestead Acts the archetypal case. Consequently, the safety-valve effect of the

frontier was able to function, so wages were kept high, which encouraged capitalists

to invest in labour-saving technologies. This path was not taken in Argentina because

the interior’s peasantries resisted the new society that was forming in the Littoral, so

Argentina lacked the kind of collective project that facilitated democratisation in the

European offshoots. For this reason, the political institutions that would have allowed

the frontier’s safety-valve effect to function did not evolve. Rather than white egalit-

arianism, Argentina emerged with positivism as its ruling ideology.

This dissertation has thus advocated a return to the more pessimistic conclu-

sions that previously reigned in the historiography of Argentina’s long nineteenth

century.4 It has reinforced that pessimism by placing the country’s uneven develop-

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ment within the context of a new metanarrative of global divergence. It has,

moreover, identified some of the problems with the data that optimistic historians

have used to make their case. It has shown, for example, that Argentina’s historical

GDP statistics are unreliable;5 the evidence on the concentration of landownership

has been misinterpreted;6 and the purchasing power of wages has been overestim-

ated.7 Finding these errors is one of this dissertation’s major empirical contributions

to Argentina’s historiography. Another has been to demonstrate the sheer magnitude

and length of the country’s nineteenth-century terms-of-trade boom, as the terms of

trade probably improved by over 2,000 percent from the 1780s to the 1900s.8 It was

this long boom, the dissertation has contended, that drove Argentina’s uneven devel-

opment, generating the oligarchic state that prevented it from realising its potential

by restricting access to the land. For this reason, Argentina’s integration into global

capitalism should not be seen as having led to a ‘golden age’ in which it became one

of the ‘richest countries in the world’. The implication of this dissertation is, there-

fore, that much of the historiography of Argentina’s twentieth century must also be

revised. In short, there has been no ‘Argentine paradox’ because the country’s early

twentieth-century ‘golden age’ is a myth.

The Bigger PictureLooking beyond Argentina, this dissertation’s main contribution has been its new

framework for understanding global divergence in the long nineteenth century. To

recap, the new metanarrative begins with Jeffrey Williamson’s account of how the

periphery experienced a terms-of-trade boom due to falling trade costs and the

4. Most notably, in Ferrer, Argentine Economy, chs. 9-12.5. This was discussed at length in Appendix 1.1. For the official estimates, the argument draws in

part on Guissarri, Argentina informal, ch. 4. Among the unofficial estimates, Cortés Conde’s(‘Estimaciones del producto’) stand out because they apparently confuse an increasing range ofgovernment taxation with output growth. See Appendix 1.1, pages 48-53.

6. Chapter 4, pages 162-63, showed how a subdivision of holdings has been confused with decon-centration. See Cortés Conde, Progreso argentino, pp. 107-17; especially as interpreted byTaylor, ‘Latifundia as Malefactor’, pp. 274-78. Chapter 4’s demonstration that this was not thecase is drawn from Sabato, Agrarian Capitalism, ch. 2. Why Taylor ignored this work is unclear.

7. As was shown in Chapter 5, pages 216-22, Williamson’s estimates of Argentina’s PPP wages(‘Evolution of Global Labor’) depend upon a highly questionable assumption about consumersbeing able to substitute between different types of goods, while Williamson also accidentallyused wholesale prices for food in Argentina and retail prices for the other countries in his sample.

8. Appendix 4.1 demonstrated this by compiling the available export price data, then dividing themby a crude proxy import price index.

- 236 -

cheaper manufactured goods being produced by the industrial revolution, which in

turn led to the land-scarce periphery’s own deindustrialisation9 – an account that this

dissertation has reinforced by underlining the methodological errors that made Willi-

amson underestimate the length, magnitude, and universality of the terms-of-trade

boom;10 in the land-scarce periphery deindustrialisation then led to the situation

described by Arthur Lewis,11 as increasing quantities of labour were applied to a

more or less fixed supply of land, bringing diminishing returns, which tended to

depress productivity levels (and per capita incomes); in the European offshoots, by

contrast, the safety-valve effect of the expanding frontier inspired capitalists to invest

heavily in labour-saving technologies, raising productivity levels (and per capita

incomes), as John Habakkuk argued.12 In this way, the world was divided into the

industrialised North Atlantic core, the prosperous European offshoots, and the ‘over-

populated’ poor periphery.

This focus on endowments of natural and human resources contrasts, in

particular, with the neo-institutionalist literature that has become prominent in the

debates about the origins of global inequality.13 Most famously, Daron Acemoglu,

Simon Johnson, and James Robinson showed a negative correlation between the

population density of Europe’s future colonies in 1500 and their GDPs per capita 500

years later.14 This, they have claimed, was because Europeans established ‘extractive’

institutions to exploit the natives in densely-populated colonies, whereas in the

poorer, more-sparsely populated colonies they established ‘inclusive’ institutions

because there were fewer natives to exploit, so they instead had to encourage settlers

to move there. The legacies of these colonial institutions, they conclude, continue to

explain why the former colonies that were densely populated in 1500 are poor today,

while those that were sparsely populated are rich.15 This dissertation, on the other

hand, offers a rather simpler explanation: during the long nineteenth-century terms-

9. Williamson, ‘Globalization and the Great Divergence’; and idem, Trade and Poverty, esp. ch. 3.10. The error, as discussed in Chapter 2, pages 64-80, was to use prices from the core countries as

proxies for prices in the peripheral countries.11. Lewis, ‘Economic Development’.12. Habakkuk, American and British Technology, esp. ch. 3.13. For useful discussions, see Bértola, ‘Institutions and the Historical Roots’; and Chang, ‘Under-

standing the Relationship’.14. Acemoglu, Johnson, and Robinson, ‘Reversal of Fortune’.15. This is the slightly modified version of their argument that is made in Acemoglu and Robinson,

Why Nations Fail, esp. Ch. 1. It appears to draw on Engerman and Sokoloff, EconomicDevelopment.

- 237 -

of-trade boom it was advantageous to have an abundance of land relative to labour,

so the sparsely-populated (that is, land-abundant) countries prospered, at the same

time as the densely-populated (that is, land-scarce) countries stagnated. It simply

became, in other words, highly beneficial to have an abundance of land.

That does not mean, however, that institutions were unimportant. Even

though endowments of land and labour set the limits to the possible, how well a

particular country did within those limits was greatly influenced by institutions.

Argentina and the United States, for example, both had high ratios of land to labour,

yet only the United States experienced rapid intensive growth. This was because

resource abundance was, in part, ‘socially constructed’, as the right institutions were

required for ‘natural’ resources to be most effectively exploited.16 Crucially, institu-

tions that gave (or restricted) access to land largely determined whether (or not) the

safety-valve effect of the expanding frontier could function. Indeed, among land-

abundant countries institutions were the principal determinant of whether they fully

exploited the opportunity presented by the long boom, as the contrasting cases of

Argentina and the United States demonstrate. This suggests, then, that a focus on

institutions helps explain divergence among similar types of countries during the

long nineteenth century, but is less appropriate for comparisons between countries

with radically different endowments of natural and human resources.

This dissertation has also shown that institutions evolve over time, especially

in response to changes in the global political economy. Here the emphasis has been

on how global capitalism reordered societies through the terms of trade. Where land

was abundant, the dissertation has contended, the long boom allowed white-egalit-

arian democracies to emerge; where it was scarce, by contrast, it was typically

conducive to far less inclusive institutions, as popular unrest had to be put down. In

much of the land-scarce periphery, this meant that the ‘imperialism of free trade’

became the ‘new imperialism’, as a series of crises led to direct European colonisa-

tion during the second half of the nineteenth century.17 For the same reason, in

Argentina the peasantries of the relatively land-scarce parts of the interior had to be

excluded from politics by the oligarchic state due to the impact of the country’s own

terms-of-trade boom. The case of Argentina in this way demonstrates how the neo-

16. David and Wright, ‘Increasing Returns’; also Wright and Czelusta, ‘Why Economies Slow’.17. Cf. Cain and Hopkins, British Imperialism, p. 28.

- 238 -

institutionalist’s focus on colonial legacies is insufficient because the country’s insti-

tutional backwardness was not a remnant of the colonial era. Rather, as this disserta-

tion has shown, Argentina’s oligarchic state formed as part of its reordering by global

capitalism.

Looking at the bigger picture, then, this dissertation has provided a new

metanarrative of global divergence, which has then been applied to the case of

Argentina. The periphery’s long terms-of-trade boom, it has argued, generated a new

global order by allowing land-abundant regions to prosper, while making land-scarce

regions stagnate. Argentina was lucky, in that it had abundant land resources, but also

unlucky because the stagnant interior strongly influenced its political institutions.

The Argentine case illustrates, therefore, how a country’s limits to the possible within

the new global order were largely set by its endowments of human and natural

resources, while institutions played a major role in determining how successful a

country was within those limits. Similarly, when the terms of trade deteriorated after

the First World War it would also create opportunities for some, but misfortune for

others, with some countries’ institutions better able to adapt than others. Saying

whether Argentina was a winner or a loser from this next global reordering would,

however, require another dissertation.

- 239 -

Data Appendix

This data appendix provides much of the quantitative evidence used in this disserta-

tion, in order to facilitate the reproduction of its results. Some researchers may also

find the data useful for other purposes. It includes the following tables:

DA.1 Argentina’s GDP Estimates, 1875-2012DA.2 Williamson’s Terms-of-Trade Series, 1750-1913DA.3 Terms-of-Trade Series for Six Countries, 1861-1913DA.4 Indonesia’s Terms of Trade, 1820-1913DA.5 India’s Terms of Trade, 1861-1913DA.6 International Exchange Rates, 1791-1938DA.7 International Commodity Prices, 1813-1913DA.8 International Freight Rates, 1757-1913DA.9 Arable Potential, Cropland, and Population, 1780-1910DA.10 Potential Arable Land and World Population, 1500-1900DA.11 Estimated Exchange Rates for Argentina, 1780-1938DA.12 Argentine Hide Prices in the Core (£ Per Ton), 1790-1938DA.13 Hide Prices in Buenos Aires, 1780-1851DA.14 Hide Prices in Buenos Aires, 1863-1938DA.15 Argentina’s Export Prices, 1780-1938DA.16 Argentina’s Export Prices, 1910-1938DA.17 Argentina’s Proxy Import Price Index, 1780-1938DA.18 The 100 Largest Corporations Registered in Argentina, 1914DA.19 Land Ownership in Buenos Aires Province, 1836-90

- 240 -

Tabl

e D

A.1

Arg

entin

a’s G

DP

Estim

ates

, 187

5-20

12

CC

CC

(rev

.)E

-PG

.1G

.2O

.1O

.2O

.3O

.4O

.5Fo

rmal

Info

rmal

Tota

lFo

rmal

Info

rmal

Tota

l19

00=1

0019

50 $

1970

$19

70 $

1950

=100

1960

=100

1970

=100

1986

=100

1993

=100

1875

26.2

17.5

1876

26.8

17.5

1877

29.5

19.7

1878

28.1

18.9

1879

29.3

20.3

1880

28.7

21.8

1881

29.2

21.9

1882

36.7

29.6

1883

41.1

33.8

1884

44.1

37.2

5,01

9.0

1885

51.7

44.7

5,32

2.0

1886

51.9

43.0

5,32

0.0

1887

55.4

46.3

5,95

8.0

1888

64.3

55.1

6,54

8.0

1889

70.5

64.4

7,67

5.0

1890

64.7

58.6

7,34

5.0

1891

61.2

51.0

6,53

5.0

1892

73.1

63.7

7,11

3.0

1893

77.5

68.1

7,46

6.0

1894

89.3

80.0

8,04

0.0

1895

99.0

82.7

8,09

3.0

1896

109.

586

.68,

768.

018

9786

.979

.18,

198.

018

9896

.485

.08,

888.

018

9911

3.3

109.

89,

666.

019

0010

0.0

100.

09,

425.

019

0110

8.8

115.

410

,222

.0

- 241 -

Tabl

e D

A.1

(con

t.)

CC

CC

(rev

.)E

-PG

.1G

.2O

.1O

.2O

.3O

.4O

.5Fo

rmal

Info

rmal

Tota

lFo

rmal

Info

rmal

Tota

l19

00=1

0019

50 $

1970

$19

70 $

1950

=100

1960

=100

1970

=100

1986

=100

1993

=100

1902

112.

211

2.9

10,0

16.0

1903

133.

913

4.1

11,4

49.0

1904

156.

315

0.4

12,6

70.0

1905

182.

916

4.3

14,3

52.0

1906

181.

016

6.4

15,0

74.0

1907

176.

916

3.5

15,3

92.0

1908

208.

018

5.0

16,9

00.0

1909

223.

919

2.5

17,7

34.0

1910

232.

919

7.4

19,0

24.0

1911

240.

619

3.5

19,3

66.0

1912

278.

823

0.1

20,9

48.0

1913

281.

623

1.0

21,1

66.0

1914

227.

220

1.0

18,9

74.0

1915

240.

321

6.3

19,0

74.0

1916

230.

820

4.5

18,5

25.0

1917

203.

617

6.6

17,0

24.0

1918

267.

222

3.5

20,1

45.0

1919

251.

022

6.6

20,8

86.0

1920

255.

423

1.7

22,4

06.0

1921

262.

023

9.8

22,9

79.0

1922

293.

326

5.7

24,8

17.0

1923

334.

929

2.5

27,5

51.0

1924

376.

531

8.3

29,7

00.0

1925

354.

730

4.9

29,5

76.0

1926

364.

232

4.7

31,0

02.0

1927

398.

435

0.4

33,2

01.0

1928

397.

835

2.4

35,2

57.0

1929

405.

335

5.8

36,8

82.0

1930

370.

732

6.9

35,3

56.0

2,57

6.0

10.0

2,58

6.0

2,57

6.0

4.1

2,58

0.0

- 242 -

Tabl

e D

A.1

(con

t.)

CC

CC

(rev

.)E

-PG

.1G

.2O

.1O

.2O

.3O

.4O

.5Fo

rmal

Info

rmal

Tota

lFo

rmal

Info

rmal

Tota

l19

00=1

0019

50 $

1970

$19

70 $

1950

=100

1960

=100

1970

=100

1986

=100

1993

=100

1931

363.

933

5.4

32,9

02.0

2,39

7.2

267.

72,

664.

92,

397.

211

7.2

2,51

4.3

1932

346.

432

3.6

31,8

12.0

2,31

7.8

584.

92,

902.

72,

317.

828

2.2

2,60

0.0

1933

352.

733

1.2

33,3

07.0

2,42

6.7

470.

32,

897.

02,

426.

721

4.4

2,64

1.1

1934

388.

035

8.8

35,9

36.0

2,61

8.2

793.

63,

411.

82,

618.

231

4.3

2,93

2.5

1935

428.

440

3.5

37,4

99.0

2,73

2.1

618.

53,

350.

62,

732.

128

1.4

3,01

3.5

24.7

1936

2,76

6.9

509.

93,

276.

82,

766.

925

6.4

3,02

3.3

26.0

1937

2,98

7.3

523.

53,

510.

82,

987.

327

5.2

3,26

2.6

27.9

1938

3,02

7.9

703.

03,

730.

93,

027.

932

2.2

3,35

0.2

27.1

1939

3,13

8.2

1,23

5.6

4,37

3.8

3,13

8.2

533.

53,

671.

727

.519

403,

074.

478

9.3

3,86

3.7

3,07

4.4

397.

53,

471.

927

.919

413,

225.

274

4.8

3,97

0.0

3,22

5.2

377.

43,

602.

628

.519

423,

376.

074

1.2

4,11

7.2

3,37

6.0

415.

33,

791.

331

.919

433,

399.

21,

004.

04,

403.

23,

399.

267

4.4

4,07

3.5

33.8

1944

3,72

9.8

700.

44,

430.

23,

729.

852

6.0

4,25

5.9

34.7

1945

3,55

0.0

919.

64,

469.

63,

550.

070

2.2

4,25

2.3

39.6

1946

3,84

5.8

756.

04,

601.

83,

845.

862

1.6

4,46

7.5

49.2

1947

4,37

3.7

1,48

7.9

5,86

1.6

4,37

3.7

1,13

3.6

5,50

7.3

60.8

1948

4,42

5.9

3,02

2.7

7,44

8.6

4,42

5.9

2,05

7.6

6,48

3.5

70.2

1949

4,22

2.9

2,70

3.0

6,92

5.9

4,22

2.9

2,15

2.4

6,37

5.3

85.4

1950

4,28

6.7

2,26

6.5

6,55

3.2

4,28

6.7

2,13

1.5

6,41

8.2

100.

074

.619

514,

453.

32,

677.

87,

131.

14,

453.

32,

047.

86,

501.

113

6.7

77.5

1952

4,22

9.2

2,77

8.5

7,00

7.7

4,22

9.2

1,92

4.5

6,15

3.8

167.

173

.619

534,

453.

32,

865.

67,

318.

94,

453.

31,

962.

06,

415.

417

7.1

77.5

1954

4,63

7.2

3,25

7.6

7,89

4.8

4,63

7.2

2,44

2.3

7,07

9.6

191.

580

.719

554,

964.

73,

029.

67,

994.

34,

964.

72,

146.

17,

110.

921

3.0

86.4

1956

5,10

2.7

1,80

1.7

6,90

4.3

5,10

2.7

1,63

8.7

6,74

1.3

262.

788

.819

575,

367.

01,

845.

37,

212.

35,

367.

01,

337.

16,

704.

132

2.3

93.4

1958

5,69

4.5

2,90

0.7

8,59

5.2

5,69

4.5

1,69

0.8

7,38

5.3

434.

399

.119

595,

326.

81,

465.

06,

791.

85,

326.

81,

068.

36,

395.

087

0.6

92.7

- 243 -

Tabl

e D

A.1

(con

t.)

CC

CC

(rev

.)E

-PG

.1G

.2O

.1O

.2O

.3O

.4O

.5Fo

rmal

Info

rmal

Tota

lFo

rmal

Info

rmal

Tota

l19

00=1

0019

50 $

1970

$19

70 $

1950

=100

1960

=100

1970

=100

1986

=100

1993

=100

1960

5,74

6.2

2,42

2.8

8,16

9.1

5,74

6.2

1,30

4.9

7,05

1.1

1,08

2.2

100.

019

616,

154.

22,

988.

49,

142.

66,

154.

21,

704.

37,

858.

51,

207.

610

7.1

1962

6,05

6.5

3,00

2.8

9,05

9.3

6,05

6.5

1,74

1.6

7,79

8.1

1,51

7.2

105.

419

635,

912.

93,

045.

78,

958.

55,

912.

91,

927.

67,

840.

510

2.9

1964

6,52

2.0

3,05

3.3

9,57

5.3

6,52

2.0

2,04

9.0

8,57

1.0

113.

519

657,

119.

63,

289.

610

,409

.27,

119.

62,

235.

89,

355.

412

3.9

1966

7,16

5.6

3,47

7.4

10,6

42.9

7,16

5.6

2,49

0.3

9,65

5.8

124.

719

677,

355.

23,

631.

410

,986

.57,

355.

22,

827.

610

,182

.812

8.0

1968

7,67

1.2

3,58

5.2

11,2

56.5

7,67

1.2

2,84

5.1

10,5

16.3

133.

519

698,

326.

33,

556.

611

,882

.88,

326.

33,

165.

711

,491

.914

4.9

1970

8,77

4.5

3,54

6.5

12,3

21.0

8,77

4.5

3,46

7.9

12,2

42.4

152.

710

0.0

1971

9,10

4.6

4,12

5.2

13,2

29.8

9,10

4.6

3,67

0.5

12,7

75.1

160.

010

3.8

1972

9,29

3.7

4,31

6.4

13,6

10.1

9,29

3.7

3,60

9.8

12,9

03.5

165.

010

5.9

1973

9,64

1.8

5,64

0.4

15,2

82.2

9,64

1.8

3,79

7.4

13,4

39.2

175.

110

9.9

1974

10,1

63.0

7,81

4.3

17,9

77.3

10,1

63.0

5,16

6.0

15,3

29.0

115.

819

7510

,102

.79,

434.

619

,537

.310

,102

.75,

716.

815

,819

.511

5.1

1976

10,1

01.5

7,34

9.3

17,4

50.8

10,1

01.5

4,58

5.3

14,6

86.8

115.

119

7710

,746

.66,

303.

417

,050

.010

,746

.64,

592.

815

,339

.412

2.5

1978

10,4

00.3

5,90

0.9

16,3

01.2

10,4

00.3

5,01

6.3

15,4

16.6

118.

519

7911

,121

.75,

390.

716

,512

.411

,121

.75,

419.

516

,541

.212

6.8

1980

11,2

99.5

6,29

9.3

17,5

98.8

11,2

99.5

6,47

4.1

17,7

73.6

128.

710

3.1

85.0

1981

10,5

34.3

7,03

2.7

17,5

67.0

10,5

34.3

6,67

2.6

17,2

06.9

120.

297

.580

.519

8210

,054

.95,

763.

915

,818

.810

,054

.95,

357.

515

,412

.411

4.3

94.5

80.0

1983

10,3

33.1

6,52

0.1

16,8

53.2

10,3

33.1

6,43

6.3

16,7

69.4

117.

798

.383

.419

8410

,605

.66,

206.

716

,812

.310

,605

.66,

712.

017

,317

.612

0.8

100.

384

.719

8510

,120

.55,

324.

815

,445

.310

,120

.56,

701.

416

,821

.911

5.6

93.3

80.3

1986

122.

210

0.0

85.3

1987

124.

810

2.5

87.6

1988

121.

610

0.5

86.6

- 244 -

Tabl

e D

A.1

(con

t.)

CC

CC

(rev

.)E

-PG

.1G

.2O

.1O

.2O

.3O

.4O

.5Fo

rmal

Info

rmal

Tota

lFo

rmal

Info

rmal

Tota

l19

00=1

0019

50 $

1970

$19

70 $

1950

=100

1960

=100

1970

=100

1986

=100

1993

=100

1989

116.

193

.580

.419

9011

6.6

92.2

78.5

1991

101.

985

.619

9211

2.4

92.4

1993

119.

410

0.0

1994

129.

610

5.8

1995

123.

710

2.8

1996

129.

010

8.5

1997

139.

811

7.3

1998

121.

819

9911

7.7

2000

116.

820

0111

1.6

2002

99.5

2003

108.

320

0411

8.0

2005

128.

920

0613

9.8

2007

151.

920

0816

2.1

2009

163.

520

1017

8.5

2011

194.

320

1219

8.0

Sour

ces:

CC

: Cor

tés C

onde

, ‘Es

timac

ione

s del

pro

duct

o br

uto’

.

CC

(rev

.): C

orté

s Con

de, E

cono

mía

arg

entin

a, p

p. 2

30-3

1, C

uadr

o A

1.

- 245 -

Tabl

e D

A.1

(con

t.)E-

P: E

CL

A, D

esar

rollo

eco

nóm

ico,

p. 3

, Cua

dro

1; a

nd d

ella

Pao

lera

, ‘H

ow th

e Arg

entin

e Ec

onom

y’, p

. 187

, Tab

le 3

7

G.1

(with

info

rmal

sect

ores

timat

edus

ing

the

supp

lyan

dde

man

dof

mon

ey)

and

G.2

(with

info

rmal

sect

ores

timat

edus

ing

elec

trici

tyco

nsum

ptio

n):

Gui

ssar

ri, A

rgen

tina

info

rmal

, ch.

4, C

uadr

os 1

3 an

d 17

.

O.1

-O.4

(offi

cial

est

imat

es):

Mar

tínez

, ‘R

ecop

ilaci

ón d

e se

ries’

, pp.

19,

21,

24,

27,

Cua

dros

3, 5

, 8, a

nd 1

1.

O.5

(offi

cial

est

imat

e): I

ND

EC, a

vaila

ble

onlin

e at

http

://w

ww

.inde

c.go

v.ar

(acc

esse

d 15

Oct

ober

201

3).

- 246 -

Tabl

e D

A.2

Will

iam

son’

s Ter

ms-

of-T

rade

Ser

ies,

1750

-191

3La

tin A

mer

ica

Eur

ope

Mid

dle

Eas

tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia

Poor periphery excl. East Asia

!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1750

32.9

1751

70.9

38.1

1752

66.0

34.9

1753

61.4

30.6

1754

57.8

31.7

1755

59.1

35.2

1756

61.3

34.0

1757

57.4

29.7

1758

57.3

27.4

1759

59.3

27.9

1760

61.1

28.4

1761

63.5

26.6

1762

68.4

22.7

1763

64.2

29.0

1764

60.8

34.9

1765

60.5

36.4

1766

61.3

35.7

1767

63.8

33.5

1768

61.3

30.4

1769

60.4

33.0

1770

59.3

29.1

1771

59.1

32.0

1772

61.2

31.1

1773

60.6

29.4

1774

63.2

31.8

- 247 -

Tabl

e D

A.2

(con

t.)La

tin A

mer

ica

Eur

ope

Mid

dle

Eas

tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia


!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1775

63.8

29.4

1776

62.2

29.4

1777

60.9

36.5

1778

59.1

35.8

1779

58.5

34.9

1780

60.8

36.4

1781

58.8

33.0

1782

60.1

30.4

33.7

101.

180

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0.8

1783

57.1

29.7

19.1

95.3

58.4

324.

517

8455

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.848

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1785

53.3

26.5

47.2

99.7

49.6

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017

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2.7

55.6

333.

617

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1.5

56.2

284.

617

8855

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57.5

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517

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7.2

60.1

259.

917

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2.7

59.7

248.

917

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2.7

79.2

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83.5

277.

817

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9.9

80.4

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5.6

72.1

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317

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9740

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0.5

88.7

221.

654

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1.6

1798

43.9

29.2

40.0

30.7

200.

895

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0.6

60.0

167.

717

9946

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3.7

84.6

207.

362

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8.7

1800

48.4

40.4

38.1

28.9

32.2

169.

088

.374

.188

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4.9

56.8

142.

8

- 248 -

Tabl

e D

A.2

(con

t.)La

tin A

mer

ica

Eur

ope

Mid

dle

Eas

tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia


!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1801

47.9

42.7

41.5

32.3

31.3

125.

790

.670

.782

.817

6.5

58.0

136.

718

0242

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5.5

101.

148

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1.9

55.3

184.

718

0344

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1.7

105.

160

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4.3

58.6

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818

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113.

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1.7

63.7

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104.

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62.2

154.

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1.8

96.1

65.4

61.8

167.

258

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0.8

1807

46.7

38.9

55.1

22.3

33.2

140.

110

4.7

53.3

50.7

157.

560

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6.7

1808

46.1

49.4

87.1

23.8

30.7

95.3

99.0

67.9

61.6

172.

264

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3.2

1809

49.1

53.3

115.

326

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2.8

95.5

71.8

59.9

163.

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1810

70.3

49.2

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010

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966

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8.2

1811

33.4

73.4

48.1

42.5

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82.2

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1814

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43.4

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769

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1817

48.9

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8.1

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810

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776

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2.6

1818

57.0

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63.9

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2074

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6.6

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82.0

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7.4

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685

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2.5

1822

86.5

147.

984

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4.5

49.8

95.9

25.6

60.9

135.

815

8.1

94.0

81.5

87.1

91.0

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718

2383

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2.5

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853

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2.7

26.6

55.3

115.

612

4.3

96.4

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0.7

1824

86.8

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789

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0.3

58.2

85.6

21.8

49.6

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118.

899

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3.2

78.6

125.

318

2587

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4.4

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812

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8.5

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918

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060

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3.2

25.4

54.5

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515

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5.2

96.2

146.

480

.012

7.3

- 249 -

Tabl

e D

A.2

(con

t.)La

tin A

mer

ica

Eur

ope

Mid

dle

Eas

tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia


!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1827

95.0

77.0

84.9

102.

099

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0.3

62.6

101.

430

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7.5

18.6

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1.9

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718

2898

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1.9

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362

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2.9

32.2

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015

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8.5

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139.

281

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1829

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2.8

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315

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2.6

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484

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4.1

1830

96.3

83.3

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568

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0.9

25.6

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218

3192

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3.3

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332

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6.5

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8.6

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3310

1.4

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6.7

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99.8

1834

92.5

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88.7

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313

4.1

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6.9

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94.3

25.4

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211

5.2

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0.9

1835

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9.6

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9.3

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9.7

123.

484

.9

- 250 -

Tabl

e D

A.2

(con

t.)La

tin A

mer

ica

Eur

ope

Mid

dle

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tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia


!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1853

117.

686

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0.3

79.4

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113

4.8

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4.9

37.7

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1854

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545

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95.6

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1856

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746

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914

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915

6.4

77.9

180.

313

1.7

99.7

117.

652

.520

4.4

185.

815

6.9

16.5

136.

870

.518

5812

9.4

82.4

83.8

54.0

109.

292

.029

6.2

145.

711

7.6

133.

098

.995

.911

2.7

86.7

150.

740

.917

0.8

152.

711

4.4

21.6

132.

779

.318

5912

9.1

81.9

81.1

55.0

104.

092

.919

8.5

144.

911

6.4

130.

493

.214

1.0

116.

110

4.1

168.

943

.715

1.2

157.

311

3.6

28.2

132.

179

.518

6012

2.3

98.1

81.2

51.0

111.

387

.031

1.3

144.

113

5.0

138.

390

.011

9.8

115.

212

0.1

190.

545

.015

6.9

171.

010

8.0

37.0

152.

376

.818

6111

7.4

98.8

83.2

48.0

119.

184

.620

4.8

143.

313

8.1

128.

888

.510

1.7

115.

411

4.3

206.

349

.217

5.5

169.

591

.938

.615

0.2

79.4

1862

104.

899

.684

.647

.010

7.4

78.0

253.

413

6.2

135.

012

3.5

90.1

116.

710

8.3

136.

116

1.0

44.6

167.

816

3.4

115.

040

.313

7.4

85.6

1863

97.5

100.

469

.451

.096

.771

.620

3.0

129.

510

5.8

125.

014

0.4

83.2

93.2

141.

813

5.4

37.2

144.

615

4.7

98.7

42.1

115.

787

.218

6481

.195

.278

.845

.085

.990

.021

1.8

123.

189

.711

8.2

200.

711

1.1

89.2

134.

610

6.0

31.3

140.

712

2.0

104.

243

.910

2.1

84.7

1865

75.3

90.0

79.5

40.0

100.

578

.719

7.6

117.

093

.611

0.1

260.

913

9.4

83.5

130.

686

.434

.512

9.4

131.

613

2.1

45.8

96.8

87.2

1866

82.0

84.8

76.1

44.0

97.6

67.6

151.

412

4.1

104.

010

5.6

122.

812

6.7

89.4

114.

990

.728

.111

3.6

134.

812

3.6

48.5

94.3

89.0

1867

72.1

79.6

85.1

47.0

123.

970

.217

3.7

118.

213

4.2

118.

321

2.1

141.

110

5.2

144.

910

3.4

42.0

108.

814

3.0

103.

651

.311

2.4

87.3

1868

77.6

74.3

80.3

54.0

132.

773

.118

2.1

119.

414

1.9

126.

214

6.4

152.

110

8.1

129.

312

5.7

48.5

121.

114

6.7

100.

554

.412

3.0

81.2

1869

81.6

80.4

65.6

49.0

142.

575

.218

1.4

116.

811

6.0

121.

712

5.8

139.

495

.712

9.2

123.

152

.912

1.2

142.

210

4.6

57.6

114.

883

.418

7080

.786

.581

.252

.014

6.4

91.9

150.

512

1.2

115.

711

2.2

150.

613

7.1

98.1

126.

210

2.4

47.7

121.

013

9.7

108.

361

.010

5.5

82.8

1871

96.6

100.

085

.914

7.9

108.

115

9.6

132.

513

0.9

137.

713

3.4

134.

410

9.3

129.

098

.556

.512

2.2

140.

799

.664

.511

1.9

86.4

1872

110.

611

6.9

86.8

138.

411

9.3

147.

212

8.5

120.

511

8.7

99.7

112.

097

.114

4.7

101.

160

.311

5.8

126.

298

.268

.310

6.8

90.8

1873

112.

413

2.9

87.6

136.

110

3.6

129.

213

3.8

118.

911

0.4

127.

210

4.5

91.8

180.

596

.065

.810

7.7

114.

394

.572

.410

3.4

94.0

1874

116.

313

9.2

74.1

143.

511

6.7

137.

712

2.8

123.

212

5.6

122.

079

.792

.220

6.2

101.

472

.710

9.3

113.

691

.676

.610

8.0

89.9

1875

120.

514

6.3

84.2

137.

912

8.7

148.

313

5.9

108.

813

9.6

130.

086

.689

.419

3.3

104.

073

.911

1.2

96.4

90.0

81.1

106.

787

.318

7610

8.3

140.

293

.815

0.3

101.

915

4.6

126.

412

0.8

143.

011

3.9

80.8

86.7

191.

910

1.4

85.3

120.

210

8.6

98.3

96.2

110.

582

.018

7711

2.8

148.

886

.015

7.7

149.

415

5.1

142.

914

5.9

161.

610

1.9

101.

688

.019

7.5

108.

511

3.4

154.

312

1.2

101.

969

.912

5.0

78.6

1878

118.

313

3.3

87.5

162.

513

4.8

159.

614

8.9

127.

415

7.1

104.

410

8.9

90.1

190.

311

5.4

106.

312

6.4

121.

895

.369

.512

1.7

80.2

- 251 -

Tabl

e D

A.2

(con

t.)La

tin A

mer

ica

Eur

ope

Mid

dle

Eas

tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia


!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1879

114.

913

0.0

85.8

160.

311

8.1

157.

314

0.8

128.

016

7.1

138.

711

7.2

91.7

180.

211

7.8

104.

912

5.3

123.

295

.378

.812

3.3

79.6

1880

118.

212

2.7

77.9

147.

095

.215

1.3

138.

812

5.9

157.

911

9.6

100.

896

.018

1.5

107.

595

.312

6.6

112.

392

.974

.411

6.8

78.5

1881

111.

710

8.7

75.7

147.

110

0.3

157.

614

1.9

131.

816

1.5

122.

196

.793

.815

8.6

103.

795

.013

2.9

106.

796

.176

.811

7.2

76.6

1882

110.

092

.184

.714

3.1

104.

415

6.6

136.

312

6.6

161.

112

3.3

97.3

90.4

155.

798

.381

.996

.813

1.2

93.6

93.0

82.7

111.

477

.318

8311

2.3

101.

185

.314

7.5

113.

715

5.4

151.

312

3.5

160.

413

1.8

97.9

94.5

142.

988

.188

.387

.113

3.0

105.

294

.980

.810

9.2

77.9

1884

117.

210

6.0

77.6

161.

211

6.0

148.

014

9.1

114.

915

6.2

125.

810

8.9

97.9

134.

295

.176

.990

.512

1.6

102.

988

.984

.810

7.3

78.9

1885

112.

098

.276

.416

1.5

118.

216

4.1

153.

811

3.0

143.

211

9.7

103.

797

.113

0.5

96.5

81.6

87.7

117.

897

.786

.487

.810

8.0

79.9

1886

100.

011

1.2

70.5

157.

214

6.6

175.

014

2.1

111.

416

2.0

118.

512

3.9

99.4

130.

510

1.3

94.2

96.5

118.

997

.286

.582

.911

2.9

82.2

1887

119.

016

4.2

67.6

156.

414

9.2

170.

014

8.9

111.

814

2.1

125.

510

7.7

84.5

167.

710

0.2

110.

411

1.9

125.

210

1.2

83.2

87.3

113.

281

.118

8812

7.0

140.

283

.014

9.0

143.

914

8.4

137.

911

8.2

151.

412

5.5

106.

982

.713

6.0

100.

910

0.6

118.

912

3.4

106.

178

.185

.811

1.9

81.4

1889

143.

116

4.4

78.1

150.

116

6.8

142.

114

4.0

113.

813

4.6

132.

710

4.0

82.0

145.

710

5.5

111.

491

.513

9.3

102.

979

.793

.711

3.0

83.7

1890

105.

016

7.3

75.4

159.

917

2.3

116.

615

0.3

107.

212

8.8

128.

410

9.8

90.2

155.

510

0.9

116.

789

.911

6.8

98.7

82.2

93.8

108.

889

.018

9111

5.5

158.

272

.815

6.5

170.

318

6.7

149.

811

6.6

131.

511

1.4

109.

891

.714

4.5

102.

112

3.3

90.8

111.

610

8.6

82.4

98.1

117.

488

.018

9212

6.1

147.

674

.014

1.2

176.

116

2.2

150.

610

4.9

130.

391

.710

5.8

92.6

123.

810

2.5

127.

392

.611

5.1

111.

779

.010

9.9

113.

086

.618

9394

.117

1.0

76.2

130.

815

8.7

129.

714

9.5

94.7

132.

794

.310

9.7

86.9

127.

898

.213

8.6

85.7

120.

091

.377

.599

.710

7.9

86.5

1894

88.0

176.

678

.512

2.5

179.

616

6.6

158.

187

.413

1.2

90.7

109.

587

.210

6.1

100.

413

3.6

71.6

104.

189

.569

.010

6.7

108.

490

.618

9566

.117

6.0

72.6

126.

018

7.0

132.

715

7.9

98.0

139.

393

.911

5.9

88.5

97.3

96.4

134.

467

.597

.888

.570

.011

5.2

107.

891

.718

9693

.015

1.1

64.9

128.

316

0.2

134.

814

2.8

104.

613

5.8

110.

310

5.8

88.7

94.7

103.

215

0.8

52.3

95.9

98.2

76.4

101.

811

3.2

90.5

1897

109.

011

7.4

74.7

115.

313

8.3

146.

312

7.9

117.

213

4.1

96.6

107.

597

.392

.010

2.7

133.

258

.390

.010

7.9

76.7

119.

611

4.6

89.3

1898

106.

198

.188

.110

6.6

138.

813

4.5

107.

012

3.9

124.

179

.712

4.2

101.

693

.710

0.7

122.

759

.810

1.5

116.

680

.311

1.1

113.

389

.318

9911

0.1

92.2

91.1

102.

989

.912

6.8

112.

910

8.4

119.

483

.711

9.0

101.

210

1.6

96.9

103.

290

.611

3.0

113.

196

.312

5.1

105.

393

.119

0010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

019

0111

4.1

91.9

127.

299

.010

2.5

117.

198

.410

2.0

112.

310

5.3

106.

799

.281

.792

.010

1.5

92.4

97.7

95.0

88.9

104.

199

.799

.019

0212

4.0

77.6

124.

684

.086

.813

5.1

103.

710

6.7

110.

399

.611

6.5

106.

777

.587

.710

3.6

95.0

105.

793

.597

.311

4.8

101.

694

.319

0311

0.1

79.4

126.

683

.481

.514

5.8

104.

010

7.7

109.

813

8.8

121.

010

2.1

83.5

94.5

112.

693

.110

0.6

108.

711

9.5

116.

910

6.4

93.2

1904

117.

098

.313

2.0

91.5

87.1

144.

610

2.6

112.

111

0.0

144.

811

0.0

97.7

87.8

100.

011

3.0

91.9

106.

698

.511

3.8

110.

710

8.8

93.3

- 252 -

Tabl

e D

A.2

(con

t.)La

tin A

mer

ica

Eur

ope

Mid

dle

Eas

tS

outh

Asi

aS

outh

east

Asi

aE

ast A

sia


!

Argentina

Brazil

Chile

Cuba

Mexico

Venezuela

Italy

Portugal

Russia

Spain

Egypt

Levant

Ottoman

Ceylon

India

Indonesia

Malaya

Philippines

Siam

China

Japan

Britain

1905

129.

010

4.3

158.

196

.289

.815

5.4

109.

411

2.8

110.

312

2.7

114.

992

.081

.998

.012

2.0

103.

311

1.9

100.

211

2.2

115.

311

0.1

93.3

1906

126.

196

.819

0.6

102.

210

7.1

146.

710

9.0

105.

512

5.1

143.

611

9.4

97.3

83.2

103.

710

3.3

127.

410

4.8

103.

611

8.9

124.

610

8.4

94.4

1907

125.

076

.518

2.7

93.0

95.2

135.

610

6.1

107.

612

0.6

152.

812

6.0

98.6

96.5

102.

698

.612

1.3

95.3

110.

712

7.1

116.

310

7.0

95.5

1908

130.

177

.416

7.3

82.3

89.0

137.

897

.511

1.3

109.

813

5.8

118.

797

.393

.298

.710

5.4

101.

787

.310

6.0

104.

411

1.5

106.

396

.619

0915

5.1

95.1

142.

380

.183

.714

3.7

99.2

124.

011

8.4

131.

412

4.4

98.2

101.

395

.711

8.6

103.

694

.410

3.5

104.

310

3.9

111.

391

.419

1014

6.1

112.

513

2.8

81.3

98.0

143.

396

.511

1.8

117.

420

1.5

121.

299

.310

7.0

102.

813

4.0

116.

795

.810

2.0

109.

093

.811

3.6

88.8

1911

137.

012

8.7

144.

284

.412

2.1

147.

492

.410

5.4

110.

416

2.2

157.

410

4.9

104.

211

0.1

148.

415

1.0

94.7

114.

410

7.8

101.

211

7.5

96.5

1912

127.

013

5.5

163.

110

2.7

120.

413

9.9

97.8

114.

610

0.2

156.

215

4.8

97.6

103.

510

8.4

145.

414

8.2

101.

513

7.2

108.

311

1.5

118.

196

.519

1312

9.0

107.

715

9.3

98.6

105.

613

8.1

99.4

108.

696

.615

9.6

161.

410

2.8

102.

710

9.1

138.

614

2.6

94.4

109.

711

0.4

107.

011

5.0

95.5

Not

e:Th

e21

serie

sar

ere

prod

uced

here

asin

Prof

esso

rWill

iam

son’

sda

taba

se.A

sin

the

orig

inal

,all

are

refe

renc

edso

that

1900

equa

ls10

0,ex

cept

Cub

a,w

hich

isre

fere

nced

soth

at18

26eq

uals

100.

Inth

eca

seof

Arg

entin

ath

ere

isa

data

entry

erro

rfor

1895

,whi

chsh

ould

read

86,a

ccor

ding

tow

hati

sm

ost

likel

yto

beW

illia

mso

n’s

root

sour

ce(d

iTel

laan

dZy

mel

man

,Eta

pas

deld

esar

rollo

,p.5

6,C

uadr

o10

).Th

eot

hers

erie

sha

veno

tbee

nch

ecke

dfo

racc

urac

yag

ains

t the

orig

inal

sour

ces.

Sour

ce:D

ata

unde

rlyin

gW

illia

mso

n,‘G

loba

lizat

ion

and

the

Gre

atD

iver

genc

e’,p

.362

,Fig

ure

2;al

soid

em,T

rade

and

Pove

rty,

p.32

,Fig

ure

3.2;

kind

lypr

ovid

ed b

y Pr

ofes

sor W

illia

mso

n.

- 253 -

Table DA.3Own-Price and Proxy Terms-of-Trade Series for Six Countries, 1861-1913

Canada China Indonesia India Italy JapanTM BHW HH W KA BHW New W FV GBB YY BHW

1861 63.9 189.01862 65.7 147.5 87.2 183.61863 57.1 124.1 84.5 147.11864 48.7 97.1 84.4 153.51865 24.9 94.2 47.3 79.1 83.8 143.31866 20.3 85.2 60.5 83.1 85.5 109.81867 79.0 93.9 30.3 92.9 58.6 94.8 92.7 125.81868 69.2 91.0 35.0 99.0 61.3 115.2 92.0 131.91869 60.3 90.8 76.1 94.8 38.2 100.3 69.1 112.8 92.0 131.41870 67.5 85.7 76.5 98.1 34.4 97.6 71.6 93.8 92.5 109.21871 61.1 88.4 75.9 90.3 40.8 109.3 72.6 90.3 97.1 115.71872 58.9 87.5 71.1 89.0 43.5 111.2 75.8 92.7 107.8 106.61873 64.4 99.2 70.8 85.6 47.5 117.7 70.4 88.0 103.0 93.61874 68.3 105.9 62.8 83.0 52.4 133.4 73.9 93.0 100.3 99.71875 70.2 102.4 65.3 81.5 53.3 134.9 78.6 95.4 99.7 107.5 75.8 107.41876 73.7 104.0 54.4 89.0 61.6 133.2 76.7 92.9 112.2 112.1 89.9 145.51877 73.9 113.7 65.2 92.3 81.9 146.4 91.6 99.4 109.5 112.4 65.3 142.91878 79.8 104.7 66.3 86.4 76.7 129.1 92.8 105.8 111.4 115.7 65.0 124.41879 78.8 97.5 69.7 86.4 75.7 122.6 92.8 107.9 113.9 114.2 73.6 118.61880 76.9 96.5 69.3 84.2 68.8 117.1 93.1 98.5 105.4 109.6 69.6 99.51881 77.3 103.7 72.8 87.1 68.5 118.8 85.9 95.0 104.3 114.2 71.8 110.51882 82.0 101.0 76.7 84.3 59.1 105.1 82.4 90.1 106.0 113.5 77.3 110.21883 83.6 98.4 75.1 86.0 63.7 110.7 82.1 80.8 107.4 112.5 75.5 114.01884 82.3 91.7 83.6 80.5 55.5 104.5 92.8 87.2 107.6 107.3 79.3 113.11885 83.0 92.1 83.3 78.2 58.9 99.8 82.8 88.5 109.7 119.0 82.0 104.41886 85.0 90.8 91.4 78.4 68.0 99.4 82.8 92.8 111.6 126.9 77.5 116.61887 88.5 86.9 62.4 75.4 79.7 134.7 77.0 91.9 107.9 123.1 81.6 121.81888 95.2 97.5 62.7 70.8 72.6 119.4 81.9 92.5 98.1 107.6 80.2 111.31889 90.8 94.8 63.0 72.3 80.4 131.2 93.5 96.7 102.4 102.9 87.6 114.41890 89.6 89.9 59.8 74.4 84.2 125.0 85.3 92.5 103.2 84.6 87.7 114.71891 94.5 95.8 56.1 74.6 89.0 124.8 81.0 93.5 101.1 135.3 91.7 114.11892 93.9 87.7 58.8 71.6 91.9 121.5 90.4 93.9 103.0 117.6 102.7 110.51893 96.8 81.8 67.0 70.2 100.0 131.4 93.5 90.0 102.5 94.0 93.2 114.61894 101.5 84.2 91.1 62.5 96.4 122.9 94.4 92.0 102.1 120.7 99.7 106.91895 95.1 88.9 96.4 63.4 97.0 116.0 92.8 88.4 107.2 96.2 107.7 107.71896 97.4 98.3 91.0 69.2 108.8 105.9 87.7 94.6 101.5 97.7 95.1 111.41897 98.0 107.7 85.7 69.5 96.2 97.6 92.3 94.1 98.5 106.0 111.7 110.51898 89.0 107.0 91.2 72.8 88.6 88.4 89.6 92.3 94.3 97.4 103.8 109.01899 95.6 98.5 68.5 87.3 74.5 89.5 76.4 88.8 99.4 91.8 116.9 113.01900 89.8 95.3 82.3 90.6 72.2 89.6 79.1 91.7 87.8 72.5 93.5 110.51901 91.1 95.9 85.4 80.6 73.3 86.2 76.7 84.3 92.1 84.9 97.3 100.51902 95.5 90.1 82.6 88.1 74.7 76.0 85.4 80.4 96.4 97.9 107.3 103.41903 95.9 90.7 85.5 108.2 81.3 77.1 85.0 86.6 98.4 105.8 109.2 115.51904 94.5 92.9 94.1 103.1 81.6 90.0 89.3 91.7 92.0 104.9 103.5 112.41905 92.0 95.4 89.8 101.6 88.1 94.9 90.2 89.9 97.0 112.6 107.8 111.21906 94.5 95.2 83.2 107.8 74.5 87.2 98.3 95.0 94.9 106.3 116.4 112.21907 93.4 92.7 84.3 115.2 71.2 81.1 95.3 94.0 96.8 98.2 108.7 114.61908 95.3 94.9 101.4 94.6 76.1 89.9 92.6 90.4 92.6 99.9 104.2 99.91909 102.1 97.5 105.1 94.5 85.6 93.4 91.9 87.7 92.8 104.2 97.1 96.61910 102.5 92.4 111.7 98.8 96.7 97.8 86.4 94.3 97.6 103.8 87.6 99.2

- 254 -

Table DA.3 (cont.)Canada China Indonesia India Italy Japan

TM BHW HH W KA BHW New W FV GBB YY BHW1911 100.4 96.3 111.7 97.7 107.1 106.5 94.6 100.9 100.2 106.8 94.5 101.81912 101.1 105.5 112.9 98.1 105.0 110.8 90.1 99.4 98.6 101.5 104.2 99.01913 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Note: For each country, the lefthand column contain the own-price series, the righthandcolumn the proxy series.

Sources:

BHW: Data underlying Blattman, Hwang, and Williamson ‘Winners and Losers’; andWilliamson, ‘Globalization and the Great Divergence’.

FV: Federico and Vasta, ‘Was Industrialization’, pp. 22-23, Table 2

GBB: Glazier, Bandera, and Berner, ‘Terms of Trade’, pp. 30-33, Table 5.

HH: Ho, Index Numbers; as corrected by Hou, Foreign Investment, pp. 194-98.

KA: Korthals Altes, Changing Economy in Indonesia, XV, pp. 158-60.

New: See Appendix 2.2 and Table DA.5 below.

TM: Taylor and Michel, Statistical Contributions, pp. 18-19

YY: Yamazawa and Yamamoto, Estimates of Long-Term Economic Statistics, XIV, pp.169-70, 193, 197.

- 255 -

Table DA.4Indonesia’s Terms of Trade, 1820-1913

Px Pi NBTT Px Pi NBTT1820 152 1871 111 272 40.81821 192 1872 117 269 43.51822 175 1873 123 259 47.51823 155 1874 129 246 52.41824 112 1875 129 242 53.31825 103 1,112 9.3 1876 133 216 61.61826 92 851 10.8 1877 158 193 81.91827 68 507 13.4 1878 135 176 76.71828 72 656 11.0 1879 131 173 75.71829 66 591 11.2 1880 128 186 68.81830 59 579 10.2 1881 122 178 68.51831 59 572 10.3 1882 104 176 59.11832 76 577 13.2 1883 109 171 63.71833 79 436 18.1 1884 91 164 55.51834 80 436 18.3 1885 86 146 58.91835 77 435 17.7 1886 85 125 68.01836 99 435 22.8 1887 102 128 79.71837 86 437 19.7 1888 98 135 72.61838 76 443 17.2 1889 111 138 80.41839 81 434 18.7 1890 112 133 84.21840 92 400 23.0 1891 113 127 89.01841 83 383 21.7 1892 113 123 91.91842 69 416 16.6 1893 121 121 100.01843 66 406 16.3 1894 108 112 96.41844 74 450 16.4 1895 98 101 97.01845 77 466 16.5 1896 111 102 108.81846 67 443 15.1 1897 100 104 96.21847 66 400 16.5 1898 93 105 88.61848 59 355 16.6 1899 76 102 74.51849 64 336 19.0 1900 83 115 72.21850 80 304 26.3 1901 85 116 73.31851 80 345 23.2 1902 74 99 74.71852 77 345 22.3 1903 78 96 81.31853 78 341 22.9 1904 84 103 81.61854 78 322 24.2 1905 96 109 88.11855 79 298 26.5 1906 82 110 74.51856 97 287 33.8 1907 84 118 71.21857 113 298 37.9 1908 86 113 76.11858 90 305 29.5 1909 89 104 85.61859 99 314 31.5 1910 89 92 96.71860 100 308 32.5 1911 106 99 107.11861 99 279 35.5 1912 106 101 105.01862 102 317 32.2 1913 100 100 100.01863 105 391 26.9 1914 109 103 105.81864 109 483 22.6 1915 141 115 122.61865 108 434 24.9 1916 152 154 98.71866 107 527 20.3 1917 139 203 68.51867 97 320 30.3 1918 110 256 43.01868 92 263 35.0 1919 300 275 109.11869 100 262 38.2 1920 503 303 166.01870 93 270 34.4 1921 201 181 111.0

- 256 -

Table DA.4Px Pi NBTT Px Pi NBTT

1922 176 182 96.7 1932 40 90 44.41923 237 181 130.9 1933 37 78 47.41924 222 179 124.0 1934 45 74 60.81925 282 173 163.0 1935 45 72 62.51926 233 163 142.9 1936 59 74 79.71927 202 157 128.7 1937 82 98 83.71928 149 152 98.0 1938 58 94 61.71929 136 151 90.1 1939 75 95 78.91930 91 142 64.1 1940 76 113 67.31931 57 112 50.9

Note: The indices represent prices in East Indies guilders.

Source: Korthals Altes, Changing Economy in Indonesia, XV, pp. 158-60.

- 257 -

Table DA.5India’s Terms of Trade, 1861-1913

Official NewPx Pi NBTT Px Pi NBTT

1861 57.1 81.2 70.4 55.9 87.5 63.91862 57.1 81.2 70.4 61.9 94.1 65.71863 60.4 96.6 62.5 71.5 125.3 57.11864 66.9 112.8 59.3 78.3 160.7 48.71865 64.9 106.8 60.8 71.0 150.2 47.31866 71.4 107.7 66.3 81.6 134.8 60.51867 66.2 106.0 62.5 69.7 119.0 58.61868 61.0 91.5 66.7 61.2 99.8 61.31869 70.1 82.9 84.6 66.5 96.2 69.11870 68.2 81.2 84.0 70.2 98.2 71.61871 61.7 75.2 82.0 63.5 87.4 72.61872 65.6 77.8 84.3 68.3 90.1 75.81873 64.9 85.5 76.0 66.4 94.4 70.41874 66.2 84.6 78.3 66.2 89.6 73.91875 61.7 76.9 80.2 63.6 80.9 78.61876 58.4 77.8 75.1 60.4 78.8 76.71877 71.4 75.2 95.0 67.6 73.7 91.61878 74.0 71.8 103.1 66.0 71.1 92.81879 72.7 70.9 102.5 67.8 73.1 92.81880 71.4 75.2 95.0 72.2 77.5 93.11881 64.3 73.5 87.5 65.5 76.3 85.91882 61.7 72.6 84.9 62.4 75.8 82.41883 60.4 67.5 89.4 60.2 73.3 82.11884 62.3 66.7 93.5 65.0 70.1 92.81885 59.1 64.1 92.2 62.6 75.6 82.81886 60.4 68.4 88.3 62.0 74.9 82.81887 61.0 70.9 86.0 59.3 77.1 77.01888 63.6 78.6 80.9 63.3 77.3 81.91889 67.5 77.8 86.8 68.5 73.3 93.51890 67.5 77.8 86.8 65.9 77.3 85.31891 66.9 71.8 93.2 61.5 75.9 81.01892 70.8 71.8 98.6 66.5 73.6 90.41893 72.7 76.1 95.6 71.4 76.4 93.51894 71.4 71.8 99.5 70.9 75.2 94.41895 72.1 74.4 96.9 69.3 74.7 92.81896 76.0 80.3 94.6 68.7 78.4 87.71897 80.5 73.5 109.5 68.3 74.0 92.31898 66.2 68.4 96.9 60.7 67.8 89.61899 64.9 74.4 87.3 56.9 74.5 76.41900 80.5 82.1 98.1 67.9 85.9 79.11901 75.3 82.1 91.8 66.1 86.1 76.71902 73.4 73.5 99.8 66.6 78.0 85.41903 66.9 75.2 88.9 66.8 78.6 85.01904 67.5 79.5 85.0 69.6 77.9 89.31905 75.3 82.1 91.8 70.0 77.5 90.21906 90.3 89.7 100.6 82.9 84.4 98.31907 94.2 99.1 95.0 89.6 94.0 95.31908 98.1 90.6 108.2 85.9 92.8 92.61909 86.4 84.6 102.1 79.7 86.7 91.91910 82.5 93.2 88.5 83.8 97.0 86.4

- 258 -

Table DA.5Official New

Px Pi NBTT Px Pi NBTT1911 88.3 96.6 91.4 94.9 100.3 94.61912 94.2 100.0 94.2 94.5 104.9 90.11913 100.0 100.0 100.0 100.0 100.0 100.0

Note: The indices represented prices in Indian rupees.

Sources:

New: See Appendix 2.2.

Official: DCIS, Index Numbers, p. c.

- 259 -

Table DA.6International Exchange Rates, 1791-1938

East Ind.guilder

Frenchfranc

Germanmark

Indianrupee

Italianlire

USdollar

per £ £ per 1,000 £ per 1,000 £ per 1,000 £ per 1,000 per £1791 4.561792 4.471793 4.511794 4.751795 4.531796 4.291797 4.441798 4.391799 4.131800 4.551801 4.381802 4.481803 4.541804 4.551805 4.351806 4.431807 4.431808 4.631809 48.75 4.571810 48.35 4.301811 55.35 3.821812 52.27 3.621813 51.59 3.751814 46.95 58.45 4.241815 46.59 55.77 4.901816 39.59 48.98 5.221817 39.94 49.61 4.601818 41.25 51.34 4.501819 40.77 50.09 4.511820 9.30 39.13 47.57 4.521821 9.80 38.88 46.07 4.821822 39.27 46.76 4.981823 11.50 38.78 46.23 4.801824 12.50 39.36 47.16 4.871825 12.90 39.66 47.67 4.831826 12.70 38.97 46.69 4.921827 12.10 39.24 47.40 4.941828 39.43 47.80 4.931829 39.04 47.46 4.861830 39.03 47.06 4.761831 39.62 47.98 4.861832 38.82 47.29 4.861833 12.60 38.69 47.57 4.791834 12.50 39.39 48.15 4.641835 12.80 39.19 47.94 4.851836 12.80 39.26 47.77 4.821837 13.10 39.20 47.77 5.101838 13.60 39.21 48.09 4.891839 13.40 39.56 48.44 4.981840 13.70 39.56 48.76 5.00

- 260 -

Table DA.6 (cont.)East Ind.guilder

Frenchfranc

Germanmark

Indianrupee

Italianlire

USdollar

per £ £ per 1,000 £ per 1,000 £ per 1,000 £ per 1,000 per £1841 13.40 39.34 49.83 4.991842 13.80 39.15 48.09 4.801843 16.40 39.00 47.77 4.791844 16.50 39.14 47.98 4.861845 16.00 38.90 47.60 4.871846 13.50 38.94 47.67 4.821847 13.70 39.19 47.80 4.791848 14.00 39.20 47.77 4.871849 14.00 39.38 47.84 4.811850 14.00 39.36 49.44 4.871851 13.20 39.90 48.83 4.911852 13.20 39.60 48.44 4.901853 12.40 39.94 49.08 4.891854 11.90 39.99 49.42 4.881855 12.30 39.73 48.91 4.891856 12.20 39.50 48.54 4.911857 11.70 39.59 48.73 4.891858 12.11 39.83 49.08 4.861859 12.09 39.85 49.45 4.901860 12.08 39.80 49.38 4.851861 12.43 39.48 48.58 109.01 4.771862 12.36 39.73 48.87 100.74 39.12 5.561863 12.10 39.63 48.87 100.24 39.02 7.081864 11.87 39.58 48.66 100.57 38.74 9.971865 12.01 39.69 48.58 98.26 39.06 7.691866 12.18 39.70 48.51 97.57 37.46 6.881867 12.34 39.71 48.54 97.25 36.51 6.751868 12.30 39.70 48.37 96.88 35.66 6.831869 12.21 39.70 48.15 97.83 37.54 6.481870 12.26 39.70 48.26 95.34 37.37 5.591871 12.16 39.12 48.33 95.16 36.95 5.461872 11.95 39.19 48.26 96.07 35.96 5.441873 12.23 39.30 48.73 93.13 34.12 5.551874 12.27 39.64 48.52 92.59 34.84 5.421875 12.31 39.65 48.26 90.19 36.20 5.591876 12.48 39.64 48.44 85.38 36.13 5.421877 12.38 39.77 48.45 86.63 36.06 5.081878 12.42 39.72 48.48 82.34 35.92 4.891879 12.40 39.60 48.52 83.17 35.40 4.851880 12.27 39.55 48.47 83.15 35.49 4.841881 12.34 39.55 48.36 82.90 38.47 4.831882 12.38 39.66 48.35 81.35 38.17 4.871883 12.41 39.60 48.42 81.40 39.10 4.851884 12.32 39.69 48.49 80.45 39.22 4.851885 12.27 39.57 48.53 76.06 39.77 4.861886 12.23 39.61 48.65 72.67 39.11 4.861887 12.12 39.50 48.63 70.41 38.68 4.851888 12.04 39.51 48.65 68.25 38.63 4.871889 11.97 39.60 48.50 69.03 38.75 4.871890 12.10 39.60 48.44 75.37 38.62 4.861891 12.19 39.60 48.60 69.72 38.48 4.86

- 261 -

Table DA.6 (cont.)East Ind.guilder

Frenchfranc

Germanmark

Indianrupee

Italianlire

USdollar

per £ £ per 1,000 £ per 1,000 £ per 1,000 £ per 1,000 per £1892 12.18 39.70 48.71 62.43 38.08 4.871893 12.10 39.67 48.53 60.61 36.50 4.861894 12.12 39.71 48.69 54.58 35.32 4.881895 12.21 39.62 48.59 56.83 37.20 4.891896 12.23 39.67 48.53 60.21 36.32 4.871897 12.13 39.73 48.61 64.19 37.36 4.861898 12.12 39.56 48.43 66.58 36.65 4.851899 12.04 39.61 48.31 66.95 35.78 4.861900 12.00 39.72 48.21 66.55 36.78 4.871901 12.09 39.64 48.46 66.61 37.46 4.871902 12.26 39.71 48.50 66.68 38.73 4.871903 12.18 39.72 48.45 66.87 39.23 4.861904 12.17 39.71 48.49 66.85 39.20 4.871905 12.08 39.73 48.46 66.84 39.32 4.871906 12.13 39.73 48.27 67.02 39.23 4.851907 12.14 39.69 48.09 66.79 39.12 4.861908 12.14 39.78 48.41 66.52 39.32 4.871909 12.10 39.72 48.48 66.84 39.16 4.871910 12.07 39.64 48.31 66.92 38.90 4.861911 12.06 39.59 48.35 67.01 38.89 4.861912 12.02 39.62 48.24 66.91 38.71 4.871913 12.03 39.61 48.17 66.96 38.37 4.871914 12.06 39.70 39.00 4.931915 11.94 37.75 34.75 4.761916 11.46 35.64 32.03 4.771917 11.43 36.41 27.95 4.761918 10.22 37.37 26.69 4.771919 11.30 30.91 25.69 4.431920 19.21 13.56 3.661921 19.37 11.16 3.851922 18.52 10.74 4.431923 13.29 10.06 4.571924 11.86 9.87 4.421925 9.87 49.29 8.24 4.831926 6.67 48.99 8.01 4.861927 8.07 48.89 10.61 4.861928 8.06 49.03 10.80 4.871929 8.06 49.02 10.78 4.861930 8.07 49.06 10.77 4.861931 8.64 52.11 11.48 4.531932 11.20 67.74 14.62 3.511933 11.88 72.03 15.84 4.241934 13.04 78.14 16.99 5.041935 13.47 82.13 16.82 4.901936 12.30 81.07 14.67 4.971937 8.18 81.32 10.64 4.941938 5.89 82.15 10.76 4.89

Sources:

East Indies guilder: van Laanen, Changing Economy, VI, pp. 123-26, Table 8, Lines 4 and 16.

French franc, German mark, Italian Lire, and US Dollar: Officer, ‘Dollar–Sterling Exchange

- 262 -

Table DA.6 (cont.)Rates’ and ‘Bilateral Exchange Rates’, Series Ee618, Ee625, Ee626, Ee629, and Ee636; andDenzel, Handbook of World Exchange Rates, pp. 15-28, 42-43.

Indian rupee: DCIS, Index Numbers, p. 18, Table 9; and Denzel, Handbook of WorldExchange Rates, pp. 53-54, Table 1.3.1.

- 263 -

Table DA.7International Commodity Prices, 1813-1913

Cotton Raw sugar Cotton shirtings

In B

omba

y (d

. per

kg)

In A

lexa

ndria

(d

. per

kg)

In L

iver

pool

* (d

. per

kg)

In J

ava

(d. p

er k

g)

In L

ondo

n (d

. per

kg)

In

Jav

a (d

. per

m2)

In M

anch

este

r (d

. per

m2)

**

In C

alcu

tta

(d. p

er k

g)

1813 13.581814 13.581815 13.58 11.181816 13.58 11.591817 13.58 9.391818 13.25 8.721819 12.94 8.831820 12.61 15.52 7.041821 12.28 14.10 6.821822 11.97 13.66 6.481823 11.64 15.54 6.261824 11.31 11.72 19.73 6.481825 11.00 11.81 31.761826 9.57 11.59 15.69 4.691827 10.34 11.55 13.62 4.471828 10.03 10.68 14.11 4.361829 9.70 10.83 13.06 3.911830 9.70 9.67 15.29 3.891831 9.63 13.54 14.98 3.991832 9.57 22.58 14.99 3.821833 9.50 28.18 3.991834 9.44 23.88 4.171835 11.22 16.73 4.551836 7.76 14.42 5.67 9.80 6.28 4.471837 7.28 15.72 23.20 4.40 8.27 5.91 3.461838 7.14 19.96 33.01 3.93 8.86 5.78 3.771839 7.89 13.94 25.07 4.06 9.21 5.75 3.861840 7.72 14.16 23.12 3.93 11.57 5.56 3.241841 6.83 10.71 18.06 3.87 9.45 5.41 3.241842 6.50 8.63 17.08 3.17 8.74 6.02 2.821843 6.22 20.09 15.72 3.13 8.74 5.12 2.881844 5.78 6.60 14.39 3.81 7.79 5.78 2.911845 5.38 11.25 17.10 4.03 7.80 6.39 2.771846 5.14 11.10 17.87 4.21 7.80 6.99 2.521847 8.08 4.29 6.61 5.73 2.681848 10.98 3.75 4.96 5.14 2.211849 13.04 3.54 5.67 4.99 2.431850 9.60 3.75 5.91 4.82 2.851851 11.15 3.68 6.14 5.42 2.751852 10.90 3.61 5.43 5.35 2.611853 9.84 3.92 6.14 5.40 2.761854 10.12 3.76 5.91 5.44 2.541855 11.76 3.95 6.85 4.86 2.411856 17.69 5.80 7.79 4.62 2.561857 13.94 6.09 9.68 5.03 2.931858 13.20 5.30 7.79 5.05 2.78

- 264 -

Table DA.7 (cont.)Cotton Raw sugar Cotton shirtings

In B

omba

y (d

. per

kg)

In A

lexa

ndria

(d

. per

kg)

In L

iver

pool

* (d

. per

kg)

In J

ava

(d. p

er k

g)

In L

ondo

n (d

. per

kg)

In

Jav

a (d

. per

m2)

In M

anch

este

r (d

. per

m2)

**

In C

alcu

tta

(d. p

er k

g)

1859 13.36 5.79 7.32 5.22 3.071860 15.43 4.95 7.56 5.14 3.141861 10.23 25.75 5.00 6.85 4.82 3.09 38.171862 13.97 34.86 4.83 6.61 5.31 4.26 38.801863 24.86 33.99 38.00 4.66 6.38 7.73 5.96 54.601864 39.71 17.01 28.98 5.40 7.56 9.43 6.76 75.121865 22.71 24.49 27.43 5.42 6.38 8.40 5.38 66.521866 26.92 17.49 31.27 4.55 6.14 9.83 5.45 56.941867 17.72 15.04 19.72 5.04 6.61 6.25 3.96 48.811868 12.46 18.00 4.66 6.61 5.07 3.39 39.581869 16.11 16.07 5.03 7.09 4.90 3.61 39.201870 19.43 15.06 4.70 7.09 5.19 3.40 39.691871 12.84 21.10 5.07 7.32 4.96 3.06 34.061872 15.75 15.86 5.07 7.09 5.02 3.28 34.761873 16.03 14.39 4.95 6.61 4.67 3.19 34.421874 13.12 18.58 4.74 6.26 4.51 3.01 31.701875 12.45 13.08 4.56 5.91 4.41 2.95 28.071876 10.98 12.07 4.28 6.14 4.04 2.64 25.911877 12.26 14.31 5.59 7.09 3.66 2.75 23.931878 11.46 15.37 4.80 5.91 3.33 2.44 22.101879 12.39 15.79 4.54 5.67 3.21 2.23 23.301880 14.09 15.17 4.59 6.02 3.51 2.49 24.591881 13.59 16.60 4.62 6.26 3.23 2.54 24.191882 12.57 14.82 18.77 4.71 6.02 3.27 2.51 23.421883 10.84 13.84 17.75 4.54 5.77 3.26 2.33 23.751884 11.73 12.56 16.62 3.51 4.13 3.12 2.30 22.541885 11.75 13.21 13.28 3.21 4.13 2.97 2.19 20.711886 10.53 13.40 14.25 2.93 3.37 2.45 2.17 22.621887 10.31 14.32 15.51 2.96 3.43 2.60 2.22 21.091888 11.19 14.20 14.90 3.03 3.78 2.64 2.25 19.911889 10.92 14.94 16.43 3.31 4.49 2.75 2.31 20.141890 11.88 15.33 15.35 2.65 3.60 2.58 2.32 20.531891 10.12 13.26 12.98 2.69 3.66 2.46 2.21 19.801892 8.05 10.55 10.62 2.77 3.78 2.37 2.01 16.521893 9.78 10.37 11.60 3.12 4.07 2.29 2.09 16.511894 7.92 10.35 10.48 2.53 3.25 2.03 1.87 14.441895 7.77 12.23 12.78 2.03 2.83 1.85 1.79 14.591896 8.83 11.07 13.37 2.56 2.95 1.90 1.84 15.931897 8.49 8.65 10.92 2.15 2.60 1.99 1.71 16.481898 7.86 9.82 9.86 2.15 2.78 2.04 1.70 15.541899 6.80 13.49 12.02 2.25 2.89 1.97 1.70 17.971900 9.84 2.31 3.01 2.20 1.95 20.711901 9.67 2.11 2.54 2.49 1.94 21.251902 9.54 1.63 2.01 2.22 1.87 19.451903 9.35 1.84 2.30 2.22 2.05 19.511904 11.19 2.05 2.72 3.15 2.28 19.251905 9.72 2.54 3.01 3.05 2.26 18.461906 11.40 1.88 2.36 3.25 2.41 22.16

- 265 -

Table DA.7 (cont.)Cotton Raw sugar Cotton shirtings

In B

omba

y (d

. per

kg)

In A

lexa

ndria

(d

. per

kg)

In L

iver

pool

* (d

. per

kg)

In J

ava

(d. p

er k

g)

In L

ondo

n (d

. per

kg)

In

Jav

a (d

. per

m2)

In M

anch

este

r (d

. per

m2)

**

In C

alcu

tta

(d. p

er k

g)

1907 11.21 1.91 2.57 3.63 2.45 23.381908 11.07 2.15 2.72 3.65 2.22 22.511909 10.92 2.16 2.89 2.71 2.31 21.061910 13.68 2.35 3.13 3.02 2.75 23.691911 15.47 2.92 3.31 2.99 2.91 26.071912 12.78 2.83 3.16 2.98 2.69 26.291913 13.96 2.53 2.59 2.77 2.68 25.79

* To convert to d per kg, multiply by 0.103.

** Egyptian cotton.

Cotton in Bombay: Select Committee on the Growth of Cotton in India, ‘Report’, pp. 375-76;and DCIS, Index Numbers, pp. 7, 9, Table 5.

Cotton in Alexandria and Liverpool: Issawi, Economic History, pp. 447-48, 518. Converted tosterling using US$ exchange rate from Table DA.6

Cotton shirtings in Java: Korthals Altes, Changing Economy, XV, pp. 27-31, Table 1A, Series27.

Cotton shirtings in Manchester: Economist, ‘Commercial History’, supplement, various years;Sandberg, ‘Movements in the Quality’, pp. 8, 10-11, Tables 1, 2, and 4; and Korthals Altes,Changing Economy, XV, p. 31, Table 1A, Series 60.

Cotton shirtings in Calcutta: DCIS, Index Numbers, pp. 7, 9, Table 5.

Raw sugar in Java: Korthals Altes, Changing Economy, XV, pp. 87-96, Table 2A, Series 27,60, 62.

Raw sugar in London: Economist, ‘Commercial History’, supplement, various years; andKorthals Altes, Changing Economy in Indonesia, XV, pp. 27-31, 87-96, Table 2A, Series 68and 69.

- 266 -

Table DA.8International Freight Rates, 1757-1913

Bal

tic

to U

K

Indo

nesi

a to

Eur

ope

Uni

ted

Sta

tes

to U

K!

Bal

tic

to U

K

Indo

nesi

a to

Eur

ope

Uni

ted

Sta

tes

to U

K!

1757 245.9 1805 304.91758 253.9 1806 282.01759 266.0 18071760 243.0 18081761 260.8 18091762 268.8 18101763 230.4 18111764 174.8 18121765 174.8 18131766 174.8 1814 1,171.81767 1815 1,226.81768 1816 754.61769 1817 208.1 393.01770 1818 251.1 982.31771 1819 248.8 448.51772 1820 210.4 702.11773 1821 216.1 509.51774 1822 215.5 468.41775 1823 247.1 1167.4 507.61776 1824 257.9 1074.0 432.81777 1825 256.8 997.8 459.81778 236.2 1826 212.7 1035.3 430.51779 247.1 1827 193.7 1086.7 419.41780 294.1 1828 190.3 964.8 358.51781 252.8 1829 203.5 958.3 341.01782 474.0 1830 192.6 906.1 347.81783 184.0 1831 224.1 900.0 424.21784 159.9 1832 191.5 893.9 340.61785 162.2 1833 176.0 887.9 303.71786 155.9 1834 191.5 895.0 315.31787 153.0 1835 191.5 874.1 297.11788 159.9 1836 191.5 874.1 343.41789 148.5 1837 191.5 854.0 359.91790 163.4 1838 187.4 822.6 421.61791 153.0 1839 201.8 808.0 362.51792 155.9 1840 192.6 790.3 445.11793 281.4 1841 182.9 808.0 276.21794 284.9 1842 141.6 758.4 195.01795 323.9 1843 141.6 638.2 230.71796 350.8 1844 149.0 611.7 209.61797 210.9 1845 161.1 630.8 226.81798 286.0 1846 172.5 747.6 249.01799 404.1 1847 243.0 736.7 294.01800 452.3 1848 143.3 720.9 153.11801 323.3 1849 627.3 149.71802 175.4 1850 627.3 117.01803 346.2 1851 546.8 120.01804 304.9 1852 546.8 144.6

- 267 -

Table DA.8 (cont.)

Bal

tic

to U

K

Indo

nesi

a to

Eur

ope

Uni

ted

Sta

tes

to U

K!

Bal

tic

to U

K

Indo

nesi

a to

Eur

ope

Uni

ted

Sta

tes

to U

K!

1853 535.5 173.1 1884 73.3 126.9 115.31854 219.5 558.0 170.3 1885 84.6 113.7 100.31855 233.3 539.9 160.7 1886 82.6 99.3 101.51856 199.5 544.3 155.9 1887 86.4 115.1 95.61857 567.6 120.6 1888 111.4 129.9 101.01858 173.1 548.4 126.8 1889 99.9 174.9 126.91859 173.1 549.3 136.6 1890 80.5 115.3 107.71860 202.9 476.0 169.7 1891 90.6 107.6 107.31861 213.8 462.6 230.7 1892 64.5 85.9 103.71862 195.5 465.2 176.7 1893 73.8 86.5 99.41863 208.1 475.2 116.3 1894 68.0 115.1 82.51864 247.1 407.4 71.4 1895 79.9 70.9 77.21865 191.5 245.4 93.0 1896 75.3 42.3 97.61866 184.6 150.1 113.9 1897 71.6 57.5 95.31867 166.8 317.8 131.0 1898 80.5 86.4 113.81868 382.4 128.6 1899 87.3 86.9 90.21869 123.2 257.2 106.0 1900 111.0 106.3 124.91870 142.5 241.4 128.3 1901 74.2 45.8 88.41871 131.5 272.1 152.0 1902 67.1 42.2 72.41872 139.1 276.8 161.5 1903 74.5 45.4 77.61873 154.8 470.2 201.2 1904 70.7 57.3 81.71874 140.2 392.2 177.2 1905 77.3 53.8 83.41875 125.4 390.9 166.5 1906 82.1 40.7 82.61876 142.0 348.9 161.8 1907 79.8 71.3 78.71877 128.4 323.6 159.2 1908 66.6 50.5 68.81878 117.2 238.3 163.6 1909 73.3 66.6 67.31879 111.1 266.8 155.6 1910 73.8 42.9 68.11880 96.2 341.2 158.6 1911 85.5 71.8 79.01881 96.2 352.9 140.3 1912 111.7 100.1 115.41882 91.9 225.4 116.6 1913 100.0 100.0 100.01883 104.8 196.8 128.1

Note: When necessary, the series were converted to sterling using the exchange rates in TableDA.6, then referenced so that 1913 equals 100.

Sources

Baltic: Harley, ‘Ocean Freight Rates’, pp. 873-75, Table 9; and. Mohammed and Williamson,‘Freight Rates’, pp. 179-81, Table 1.

Indonesia: Korthals Altes, Changing Economy XV, pp. 159-60.

United States: North, ‘Role of Transportation’, p. 236, Table 2.

- 268 -

Table DA.9Arable Potential, Cropland, and Population, 1780-1910

Arablepotential*

Cropland (1,000 ha) Population (1,000)1780 1910 1780 1910

Afghanistan 3,039 360 2,709 2,998 5,730Albania 834 174 291 391 874Algeria 12,834 1,081 4,073 2,376 6,887Angola 88,105 220 1,016 2,316 2,721Argentina 90,571 107 7,701 300 7,055Armenia 422 240 351 465 906Australia 124,913 0 8,849 250 4,540Austria 3,348 1,367 1,812 2,969 6,648Azerbaijan 3,929 675 1,436 743 2,103Bangladesh 9,401 3,549 7,385 18,164 31,299Belarus 17,185 2,605 5,542 1,986 5,623Belgium 2,401 531 957 3,076 7,424Belize 984 7 19 15 41Benin 9,753 639 413 1,569 989Bhutan 18 12 33 30 81Bolivia 61,917 334 822 930 2,009Botswana 9,173 106 234 144 312Brazil 549,389 272 2,498 2,421 22,274Brunei 259 2 4 11 24Bosnia & Herzegovina 2,708 371 700 617 1,560Bulgaria 7,763 1,575 2,498 1,790 3,802Burkina Faso 20,341 745 891 1,689 1,968Burundi 1,414 240 361 808 1,185Cambodia 12,212 430 1,285 2,003 3,070Cameroon 35,910 1,817 2,173 1,849 2,154Canada 125,317 44 30,106 690 7,239Central African Rep. 47,887 338 713 312 640Chad 33,051 1,446 2,147 1,534 2,219Chile 3,327 359 1,682 741 3,384China 201,647 81,432 98,118 277,094 423,000Colombia 65,536 1,177 1,993 1,248 4,890Congo 167,831 235 351 453 658Congo, Dem. Rep. 22,995 3,510 4,927 8,088 11,064Costa Rica 1,205 15 133 43 374Cote d'Ivoire 26,226 243 908 256 793Croatia 3,716 609 1,149 893 2,257Cuba 7,494 74 492 332 2,150Cyprus 433 58 106 110 270Czech Rep. 6,500 1,470 2,056 2,549 4,773Denmark 3,594 885 1,988 960 2,890Djibouti 0 0 0 26 30Dominican Rep. 2,169 40 249 141 849Ecuador 12,864 903 1,263 500 1,617Egypt 121 1,091 1,572 487 712El Salvador 864 27 228 155 1,002Eq. Guinea 1,646 103 151 128 183Eritrea 590 77 144 198 361Estonia 2,181 290 815 238 897Ethiopia 42,945 1,269 6,440 2,766 13,676Falkland Is. 0 0 0 1 2

- 269 -

Table DA.9 (cont.)Arable

potential*Cropland (1,000 ha) Population (1,000)1780 1910 1780 1910

Fiji 337 37 72 99 185Finland 13,839 740 2,076 818 3,072France 38,806 18,764 21,641 26,723 41,280French Guiana 6,627 1 2 4 17Gabon 17,873 73 113 254 382Gambia 785 54 47 0 82Georgia 2,378 388 826 886 2,509Germany 28,125 5,468 12,295 20,882 62,884Ghana 18,321 1,039 1,159 2,210 2,402Greece 6,479 1,358 2,643 2,041 5,320Guatemala 3,710 225 529 628 1,441Guinea 13,217 402 425 1,226 1,263Guinea-Bissau 2,306 108 121 230 250Guyana 13,305 293 281 145 321Haiti 846 86 537 296 1,809Honduras 3,424 84 413 118 564Hong Kong 24 0 0 17 485Hungary 8,040 2,082 4,486 2,795 7,118Iceland 0 3 3 58 80India 206,327 67,271 121,819 191,840 264,044Indonesia 71,233 2,905 14,186 11,500 45,800Iran 4,709 6,063 10,073 6,033 12,967Iraq 4,406 917 1,880 1,001 2,657Ireland 4,861 3,369 2,758 4,000 4,385Israel 720 85 107 316 515Italy 16,764 8,209 11,998 17,617 34,487Jamaica 156 40 140 246 834Japan 12,861 1,750 3,185 28,400 50,368Jordan 563 34 83 72 228Kazakhstan 7,313 598 5,555 1,589 3,755Kenya 15,845 844 2,003 2,525 4,611Korea, North 3,627 688 969 3,539 4,670Korea, South 3,931 546 825 7,129 10,096Kuwait 1 1 1 128 146Kyrgyzstan 864 575 1,088 694 1,402Lao 5,900 215 431 680 1,455Latvia 5,395 262 1,027 327 1,715Lebanon 269 71 99 359 645Lesotho 362 43 150 106 358Liberia 6,294 103 123 192 224Libya 2,464 495 940 2,376 7,026Lithuania 5,481 694 2,718 381 1,999Luxembourg 143 33 64 100 260Macedonia, TFYR 1,007 211 485 282 868Madagascar 35,602 545 981 1,364 2,394Malawi 6,771 166 397 507 1,180Malaysia 12,828 358 1,389 759 2,870Mali 26,513 750 1,195 2,398 3,726Malta 39 8 14 92 214Mauritania 1,381 112 182 358 565Mexico 52,162 3,198 9,458 6,685 15,160Moldova 2,852 1,314 2,795 1,052 2,977

- 270 -



Mongolia 177 158 460 611 913Morocco 12,270 990 3,807 1 1Mozambique 63,544 634 1,368 1,897 3,988Myanmar 24,487 1,835 7,150 5,800 13,800Namibia 11,889 92 331 217 400Nepal 2,269 259 792 3,587 5,630Neth.Antilles 17 1 2 17 45Netherlands 1,856 376 658 2,034 5,951New Zealand 8,637 249 1,461 175 1,000Nicaragua 5,546 91 380 141 573Niger 10,278 4,418 7,155 1,356 2,139Nigeria 66,230 13,652 19,417 22,482 31,154Norway 2,238 286 640 796 2,392Oman 1 27 30 302 440Pakistan 5,442 5,571 7,435 15,826 20,580Panama 2,363 36 167 74 337Papua New Guinea 14,108 110 223 1,360 1,411Paraguay 21,589 83 298 280 775Peru 43,363 866 1,450 1,376 5,332Philippines 9,342 189 1,740 1,867 8,816Poland 27,980 7,081 16,271 8,657 26,644Portugal 5,027 1,434 2,346 2,791 6,115Puerto Rico 114 11 154 86 1,209Qatar 1 0 0 12 19Romania 17,383 4,102 7,497 4,848 11,866Russian Fed. 282,569 39,917 120,881 22,087 89,007Rwanda 746 158 299 770 1,419Saudi Arabia 1 3 13 2,061 2,670Senegal 13,270 409 434 1,129 1,165Serbia & Montenegro 6,444 1,242 2,982 1,600 5,226Sierra Leone 3,955 119 199 18 384Slovenia 1,010 77 145 342 864Solomon Islands 446 8 25 19 59Somalia 2,381 37 275 959 1,546South Africa 28,097 48 2,274 541 5,535Spain 24,481 11,155 15,175 10,936 19,925Sri Lanka 3,717 97 954 1,313 4,029Sudan 86,728 1,767 5,488 4,694 7,485Suriname 9,273 13 18 35 108Swaziland 805 15 45 43 127Sweden 13,891 1,361 2,656 1,909 4,991Switzerland 1,093 185 331 1,565 3,754Syrian Arab Rep. 5,636 2,580 2,925 1,308 1,919Tajikistan 1,896 533 808 611 1,234Tanzania 67,285 1,468 2,176 2,555 3,689Thailand 32,198 474 3,104 2,894 8,310Togo 4,291 631 755 550 641Trinidad & Tobago 321 1 38 12 331Tunisia 3,310 551 2,006 786 2,204Turkey 25,318 12,108 12,794 9,511 13,000Turkmenistan 759 996 1,512 483 975United Arab Emirates 1 5 6 40 61

- 271 -



Uganda 14,169 1,219 1,458 2,135 2,488Ukraine 51,897 10,037 31,144 7,468 30,837United Kingdom 15,659 2,284 6,499 10,941 41,699United States 354,315 4,249 167,897 4,493 91,604Uruguay 14,245 78 785 45 1,043Uzbekistan 4,345 2,437 3,699 2,518 5,086Venezuela 55,092 812 1,511 553 2,382Viet Nam 11,594 668 3,127 5,367 19,335Western Sahara 1 0 0 3,700 12,343Yemen 5 902 927 2,466 3,280Zambia 58,471 627 1,497 412 959Zimbabwe 24,575 249 930 488 1,775

* 1,000 hectares of arable land potentially suitable for rain-fed agriculture.

Sources: Bort, Nachtergaele, and Young, ‘Land Resource Potential’, pp. 37-38; and vanDrecht and de Vos, ‘HYDE 3.1’.

- 272 -

Table DA.10Potential Arable Land and World Population, 1500-1900

Country Arable pot.* 1500 1600 1700 1800 1900Afghanistan 3,039 2,000 2,500 2,500 3,136 5,289Albania 834 200 200 300 414 800Algeria 12,834 1,500 2,250 1,750 2,533 6,421Angola 88,105 2,008 2,134 2,259 2,331 2,667Argentina 90,571 300 300 300 300 4,989Armenia 422 218 261 309 516 861Australia 124,913 254 254 250 252 3,838Austria 3,348 2,000 2,100 2,120 3,064 6,004Azerbaijan 3,929 465 558 651 872 1,941Bangladesh 9,401 9,600 12,480 15,360 18,913 29,165Belarus 17,185 576 720 960 2,331 5,191Belgium 2,401 1,250 1,500 1,750 3,407 6,694Belize 984 7 8 8 18 37Benin 9,753 3,000 3,100 2,977 1,337 969Bhutan 18 15 20 25 31 73Bolivia 61,917 900 800 800 966 1,744Botswana 9,173 80 86 92 162 293Brazil 549,389 1,000 1,000 1,220 2,928 17,671Brunei 259 4 5 6 14 23Bosnia & Herzegovina 2,708 360 440 440 668 1,408Bulgaria 7,763 800 1,250 1,250 1,964 3,252Burkina Faso 20,341 1,280 1,451 1,644 1,700 1,928Burundi 1,414 650 715 780 813 1,111Cambodia 12,212 1,500 1,665 1,830 2,047 2,865Cameroon 35,910 1,378 1,575 1,800 1,861 2,111Canada 125,317 200 200 200 967 5,511Central African Rep. 47,887 274 288 303 314 560Chad 33,051 834 973 1,112 1,639 2,166Chile 3,327 600 600 602 781 2,931China 201,647 91,714 98,545 99,929 293,502 400,000Colombia 65,536 4,000 1,260 800 1,360 3,998Congo 167,831 333 381 435 458 625Congo, Dem. Rep. 22,995 5,888 6,256 6,624 8,488 10,801Costa Rica 1,205 450 8 23 50 301Cote d'Ivoire 26,226 340 389 445 223 569Croatia 3,716 540 660 660 967 2,037Cuba 7,494 25 50 100 448 1,635Cyprus 433 200 120 110 110 234Czech Rep. 6,500 2,160 3,240 3,240 2,376 4,398Denmark 3,594 600 700 800 1000 2561Djibouti 0 22 23 24 26 29Dominican Rep. 2,169 200 98 102 153 673Ecuador 12,864 600 500 499 500 1,400Egypt 121 4,000 5,000 4,500 3,500 10,795El Salvador 864 92 100 109 202 784Eq. Guinea 1,646 112 119 126 128 171Eritrea 590 116 131 145 212 344Estonia 2,181 63 66 69 324 862Ethiopia 42,945 2,355 2,355 2,355 2,868 12,487Falkland Is. 0 0 0 1 1 2Fiji 337 53 59 65 109 177

- 273 -

Table DA.10 (cont.)Country Arable pot.* 1500 1600 1700 1800 1900

Finland 13,839 100 200 400 978 2,674France 38,806 14,867 18,314 21,992 27,876 40,519French Guiana 6,627 2 2 2 5 15Gabon 17,873 166 189 216 265 365Gambia 785 0 0 0 0 55Georgia 2,378 568 681 795 1040 2316Germany 28,125 9,000 12,000 13,000 22,871 54,388Ghana 18,321 1,982 2,265 2,589 2,124 2,354Greece 6,479 1,000 1,500 1,500 2,177 4,962Guatemala 3,710 800 600 700 611 1,300Guinea 13,217 1,270 1,451 1,658 1,137 1,238Guinea-Bissau 2,306 206 236 269 221 245Guyana 13,305 90 90 100 159 296Haiti 846 200 40 50 463 1,560Honduras 3,424 58 72 90 126 524Hong Kong 24 13 13 12 18 306Hungary 8,040 1,250 1,250 1,500 3,119 6,532Iceland 0 60 50 50 61 79India 206,327 82,000 106,600 131,200 207,000 284,500Indonesia 71,233 7,750 8,500 9,500 12,500 38,000Iran 4,709 4,000 5,000 5,000 6,291 11,980Iraq 4,406 1,000 1,250 1,000 1,002 2,325Ireland 4,861 800 1,250 2,500 5,200 4,469Israel 720 230 230 184 348 505Italy 16,764 9,000 13,273 13,481 18,853 32,246Jamaica 156 18 36 72 335 736Japan 12,861 12,300 17,000 26,700 28,000 44,774Jordan 563 87 87 69 72 182Kazakhstan 7,313 1,340 1,530 1,720 1,556 2,973Kenya 15,845 1,500 1,750 2,000 2,703 4,381Korea, North 3,627 1,440 1,800 2,250 3,921 4,623Korea, South 3,931 2,560 3,200 4,000 8,184 9,896Kuwait 1 69 135 117 131 145Kyrgyzstan 864 350 400 450 773 1,328Lao 5,900 400 500 600 700 1,500Latvia 5,395 86 91 95 445 1,543Lebanon 269 435 508 435 345 639Lesotho 362 62 71 81 113 318Liberia 6,294 169 178 187 194 220Libya 2,464 500 500 500 494 685Lithuania 5,481 100 106 111 519 1,799Luxembourg 143 62 63 64 112 247Macedonia, TFYR 1,007 180 220 220 301 772Madagascar 35,602 700 850 1,000 1,460 2,274Malawi 6,771 357 387 418 528 1,062Malaysia 12,828 396 495 594 800 2,455Mali 26,513 1,083 1,264 1,444 2,566 3,602Malta 39 20 40 70 100 190Mauritania 1,381 258 301 344 384 546Mexico 52,162 25,000 1,000 4,000 7,357 13,615Moldova 2,852 312 390 520 1,234 2,748Mongolia 177 600 600 600 615 830Morocco 12,270 1,500 2,250 1,750 2,533 6,544

- 274 -


Mozambique 63,544 1,000 1,250 1,500 1,997 3,753Myanmar 24,487 4,000 4,500 5,000 6,000 12,500Namibia 11,889 131 140 151 238 381Nepal 2,269 2,000 2,500 3,000 3,734 5,283Neth.Antilles 17 2 5 9 19 42Netherlands 1,856 1,086 1,543 2,000 2,089 5,180New Zealand 8,637 80 140 200 172 833Nicaragua 5,546 68 75 81 162 502Niger 10,278 822 959 1,096 1,454 2,066Nigeria 66,230 11,000 14,000 18,000 22,938 30,116Norway 2,238 400 500 600 854 2,240Oman 1 200 235 270 310 418Pakistan 5,442 8,500 11,050 13,600 16,479 20,168Panama 2,363 31 39 49 82 263Papua New Guinea 14,108 1,207 1,264 1,324 1,369 1,408Paraguay 21,589 200 200 200 300 600Peru 43,363 4,000 1,300 1,500 1,346 4,836Philippines 9,342 500 800 1,250 2,022 7,324Poland 27,980 4,000 5,000 6,000 9,502 24,750Portugal 5,027 1,207 1,925 1,981 3,033 5,617Puerto Rico 114 5 7 10 146 981Qatar 1 3 3 8 13 18Romania 17,383 2,000 2,000 2,500 5,566 11,000Russian Fed. 282,569 7,560 9,450 10,710 24,931 71,523Rwanda 746 600 660 720 775 1324Saudi Arabia 1 2,000 2,250 2,000 2,076 2,581Senegal 13,270 972 1,215 1,518 1,048 1,142Serbia & Montenegro 6,444 990 1,210 1,210 1,697 4,750Sierra Leone 3,955 6 7 8 22 247Slovenia 1,010 231 239 248 370 779Solomon Islands 446 3 3 3 30 57Somalia 2,381 778 827 876 979 1,469South Africa 28,097 516 602 860 461 4,126Spain 24,481 6,500 8,500 8,000 11,552 18,594Sri Lanka 3,717 1,000 1,250 1,500 1,262 3,490Sudan 86,728 4,000 4,300 4,600 4,713 7,111Suriname 9,273 15 16 17 41 97Swaziland 805 13 15 21 51 117Sweden 13,891 800 1,000 1,500 2,120 4,615Switzerland 1,093 800 1,000 1,250 1,656 3,316Syrian Arab Rep. 5,636 1,065 1,243 1,250 1,323 1,954Tajikistan 1,896 310 350 390 681 1,169Tanzania 67,285 1,750 2,125 2,500 2,572 3,505Thailand 32,198 2,020 2,272 2,525 3,002 7,005Togo 4,291 410 469 536 554 628Trinidad & Tobago 321 0 0 0 27 268Tunisia 3,310 800 1000 800 788 1,889Turkey 25,318 6,250 8,000 8,500 9,788 12,740Turkmenistan 759 240 280 310 538 924United Arab Emirates 1 31 42 53 38 58Uganda 14,169 1,500 1,750 2,000 2,149 2,438Ukraine 51,897 2,748 3,435 4,580 8,321 25,000United Kingdom 15,659 4,200 5,000 6,839 12,060 37,844

- 275 -


United States 354,315 1,887 779 927 6,314 76,215Uruguay 14,245 24 27 30 50 915Uzbekistan 4,345 1,260 1,440 1,620 2,806 4,818Venezuela 55,092 400 400 500 567 2,353Viet Nam 11,594 2,000 2,500 3,000 5,959 17,133Western Sahara 1 0 1 1 1 1Yemen 5 2,250 2,500 2,250 2,529 3,170Zambia 58,471 303 329 355 429 863Zimbabwe 24,575 340 369 398 589 1,597

* 1,000 hectares of arable land potentially suitable for rain-fed agriculture.

Sources: Bort, Nachtergaele, and Young, ‘Land Resource Potential’, pp. 37-38; and vanDrecht and de Vos, ‘HYDE 3.1’.

- 276 -

Table DA.11Estimated Exchange Rates for Argentina, 1780-1938

Grams ofsilver in

peso

Grams ofsilver per

£ inLondon

Pesos per£ (est.)*

Pesos per£

Goldpesos(o$s)per £

Paper pesos (m$n) per £

Market Exporters Importers

1780 24.433 107.3 4.391781 24.433 101.7 4.161782 24.433 98.7 4.041783 24.433 101.9 4.171784 24.433 108.3 4.431785 24.245 111.3 4.591786 24.245 109.3 4.511787 24.245 108.8 4.491788 24.433 108.2 4.431789 24.433 109.4 4.481790 24.433 109.9 4.501791 24.433 109.6 4.491792 24.433 107.8 4.411793 24.433 111.0 4.541794 24.433 112.6 4.611795 24.433 109.6 4.491796 24.433 108.6 4.441797 24.433 109.3 4.471798 24.433 113.7 4.651799 24.433 105.9 4.341800 24.433 100.5 4.111801 24.433 97.1 3.981802 24.433 102.0 4.181803 24.433 102.7 4.201804 24.433 103.4 4.231805 24.433 98.5 4.031806 24.433 101.0 4.131807 24.433 102.5 4.191808 24.433 101.1 4.141809 24.433 99.7 4.081810 24.433 98.4 4.031811 24.433 97.1 3.981812 24.433 90.0 3.681813 24.809 84.5 3.401814 24.809 91.8 3.701815 24.809 91.0 3.671816 24.809 113.0 4.56 4.211817 24.809 110.4 4.45 4.621818 24.809 106.8 4.31 3.661819 24.809 108.0 4.35 4.401820 24.809 114.3 4.61 4.441821 24.809 117.0 4.72 4.211822 24.809 116.5 4.701823 24.809 117.0 4.71 5.271824 24.809 114.6 4.62 6.031825 24.809 113.4 4.57 5.601826 7.951827 16.961828 14.94

- 277 -

Table DA.11 (cont.)Grams ofsilver in

peso

Grams ofsilver per

£ inLondon

Pesos per£ (est.)*

Pesos per£




1829 25.331830 33.841831 34.011832 33.601833 35.031834 33.751835 35.041836 34.291837 38.431838 42.551839 66.571840 100.411841 89.551842 81.701843 78.961844 64.691845 73.691846 100.981847 100.791848 113.551849 96.071850 70.381851 82.041852 84.931853 99.711854 99.011855 106.071856 103.071857 96.711858185918601861186218631864 4.841865 4.891866 4.811867 4.941868 4.891869 4.781870 4.791871 4.751872 4.691873 4.851874 4.781875 4.791876 4.741877 4.761878 4.771879 4.79

- 278 -


peso

Grams ofsilver per

£ inLondon

Pesos per£ (est.)*

Pesos per£




1880 4.761881 4.761882 4.731883 4.761884 5.111885 5.311886 5.061887 5.061888 5.031889 5.011890 4.981891 4.951892 5.011893 5.031894 5.001895 5.011896 5.021897 5.061898 5.021899 4.971900 5.001901 4.991902 5.001903 4.981904 4.991905 4.981906 4.991907 4.971908 4.981909 5.001910 5.001911 5.001912 4.981913 4.98 11.51914 4.97 11.61915 4.91 11.41916 4.71 11.31917 10.91918 10.71919 10.21920 9.31921 12.01922 12.31923 13.31924 12.81925 12.01926 12.01927 11.51928 11.51929 11.61930 13.3

- 279 -


peso

Grams ofsilver per

£ inLondon

Pesos per£ (est.)*

Pesos per£




1931 15.51932 13.71933 13.41934 15.5 17.61935 15.5 17.31936 15.4 17.21937 15.2 16.11938 15.6 16.7

* Calculated by dividing the grams of silver per £ in London by the grams of silver in thepeso.

Note: When monthly data were given in the sources, any gaps in the series were interpolatedexponentially, then annual averages were calculated.

Sources:

Grams of silver in peso: Álvarez, Temas de historia, pp. 80-124; as compiled by Rodolfo G.Frank, available online at http://www.anav.org.ar/sites_personales/5/MONEDA.XLS(accessed 2 May 2013).

Silver market price in London: R.W. Jastram, Silver: The Restless Metal, New York, 1981,Table 15 and App. C; reproduced by Gregory Clark and Peter Lindert, available online athttp://gpih.ucdavis.edu/files/England_1209-1914_(Clark).xls (accessed 3 May 2013). Actualexchange rate: Reber, ‘British Mercantile Houses’, p. 313, Table 21.

Gold pesos (o$s) per £: Schneider, Schwarzer, and Denzel, Währungen der Welt, VII, pp.212-18.

Paper pesos (m$n) per £: Balboa, ‘Evolución del balance’, p. 160.

- 280 -

Table DA.12Argentine Hide Prices in the Core (£ Per Ton), 1790-1938

City: London Hamburg London Boston London Hamburg LondonType: Dry Dry Dry Dry Dry Salted Salted

Source: GRS JR.1 HD P S.1 JR.1 S.21790 651791 601792 511793 531794 721795 491796 541797 601798 691799 851800 791801 811802 671803 781804 711805 681806 631807 631808 591809 611810 821811 501812 601813 731814 88 1031815 87 991816 73 991817 73 881818 69 92 801819 68 100 801820 68 105 801821 77 100 901822 85 101 1001823 85 102 921824 81 94 901825 82 108 931826 78 98 901827 91 95 951828 99 96 1001829 72 94 871830 68 88 871831 69 88 861832 74 82 891833 72 80 911834 67 77 881835 55 75 751836 57 71 771837 59 75 741838 55 75 731839 63 78 76

- 281 -

Table DA.12 (cont.)City: London Hamburg London Boston London Hamburg London

Type: Dry Dry Dry Dry Dry Salted SaltedSource: GRS JR.1 HD P S.1 JR.1 S.2

1840 77 84 88 671841 67 76 75 671842 60 68 65 611843 56 65 61 60 331844 58 68 68 59 381845 57 69 68 62 391846 52 67 56 60 371847 47 61 57 54 341848 43 51 45 44 311849 41 52 49 42 301850 41 53 59 45 321851 56 62 53 351852 55 67 51 341853 80 59 441854 95 68 491855 104 80 53 551856 120 99 63 731857 141 124 83 781858 112 101 60 641859 118 103 68 731860 110 106 74 731861 92 92 65 641862 98 85 63 601863 89 73 52 531864 74 71 52 531865 81 67 49 511866 88 64 49 511867 91 64 50 511868 93 71 56 551869 100 73 53 511870 107 76 56 531871 113 83 601872 121 96 691873 118 101 761874 118 96 731875 100 85 731876 89 69 641877 102 78 711878 93 78 621879 95 73 621880 96 87 691881 108 83 641882 110 83 641883 107 83 641884 108 83 641885 103 80 601886 95 73 531887 87 71 571888 77 62 451889 73 57 461890 64 53 51

- 282 -

Table DA.12 (cont.)City: London Hamburg London Boston London Hamburg London

Type: Dry Dry Dry Dry Dry Salted SaltedSource: GRS JR.1 HD P S.1 JR.1 S.2

1891 61 51 471892 51 421893 51 451894 51 441895 65 571896 62 511897 60 511898 64 561899 68 571900 75 571901 78 551902 79 591903 73 601904 76 621905 83 671906 92 711907 90 701908 76 541909 85 641910 90 701911 90 691912 96 771913 114 871914 121 871915 119 1011916 135 1221917 184 1471918 185 1271919 207 1781920 188 1681921 89 821922 84 821923 87 751924 92 791925 105 811926 95 731927 113 961928 142 1091929 97 761930 62 601931 51 541932 45 441933 48 431934 44 451935 47 471936 57 551937 80 691938 61 51

Sources:

GRS: Gayer, Rostow, and Schwartz, Growth and Fluctuation.

- 283 -

Table DA.12 (cont.)JR: Jacobs and Richter, Großhandelpreise in Deutschland, pp. 68-69.

HD: Halperín Donghi, ‘Expansión ganadera’, p. 65.

P: US Senate, Wholesale Prices, p. 141.

S: Sauerbeck, ‘Prices of Commodities and the Precious Metals’, p. 640; idem, ‘Prices ofCommodities in 1898’, Journal of the Statistical Society of London, 62:1, 1899, p. 192;‘Prices of Commodities in 1912’, Journal of the Statistical Society of London, 76:4, 1913, p.408; Editor of the ‘Statist’, ‘Wholesale Prices in 1917’, Journal of the Statistical Society ofLondon, 81:2, 1918, p. 348; idem, ‘Wholesale Prices of Commodities in 1924’, Journal of theStatistical Society of London, 88:2, 1925, p. 277; and idem, ‘Wholesale Prices in 1939’,Journal of the Royal Statistical Society, 103:3, 1940, p. 360.

- 284 -

Tabl

e D

A.13

Hid

e Pr

ices

in B

ueno

s Aire

s, 17

80-1

851

Type:

Dry

hid

es(p

esos

per

35

lb)

Sal

ted

hide

s(p

esos

per

60

lb)

Dry

hid

es(£

per

ton)

*S

alte

d hi

des

(£ p

er to

n)**

Source:

MP.

1P.

2B

.1B

.2B

.3P.

3B

.4M

P.1

P.2

B.1

B.2

B.3

P.3

B.4

1780

1.1

1517

811.

015

1782

1.0

1517

831.

218

1784

1.5

2017

851.

115

1786

1.0

1417

871.

318

1788

1.3

1817

891.

217

1790

0.6

917

911.

116

1792

1.0

1417

931.

014

1794

1.2

1617

951.

824

1796

1.8

2417

9717

9817

9918

0018

0118

0218

0318

0418

0518

06

- 285 -

Tabl

e D

A.13

(con

t.)Type:

Dry

hid

es(p

esos

per

35

lb)

Sal

ted

hide

s(p

esos

per

60

lb)

Dry

hid

es(£

per

ton)

*S

alte

d hi

des

(£ p

er to

n)**

Source:

MP.

1P.

2B

.1B

.2B

.3P.

3B

.4M

P.1

P.2

B.1

B.2

B.3

P.3

B.4

1807

1808

1809

1810

1.5

2318

111.

523

1812

2.5

4218

132.

546

1814

2.5

4218

152.

542

1816

4.0

5518

174.

056

1818

4.0

5818

194.

057

1820

4.0

5418

216.

05.

45.

079

7138

1822

6.0

5.8

5.3

7977

4118

236.

06.

35.

671

7439

1824

6.0

6218

2518

2618

2718

2818

2923

.317

.657

2518

3034

.326

.263

2818

3131

.421

.757

2318

3231

.121

.058

2318

3332

.823

.258

2418

3433

.523

.562

2518

3532

.222

.857

24

- 286 -

Tabl

e D

A.13

(con

t.)Type:

Dry

hid

es(p

esos

per

35

lb)

Sal

ted

hide

s(p

esos

per

60

lb)

Dry

hid

es(£

per

ton)

*S

alte

d hi

des

(£ p

er to

n)**

Source:

MP.

1P.

2B

.1B

.2B

.3P.

3B

.4M

P.1

P.2

B.1

B.2

B.3

P.3

B.4

1836

30.9

22.2

5623

1837

32.6

24.0

5323

1838

32.3

23.5

4720

1839

38.0

30.8

3617

1840

41.5

1518

4161

.867

.355

.043

4722

1842

56.4

60.3

51.5

4346

2318

4354

.457

.952

.443

4624

1844

45.1

49.3

44.8

4347

2518

4539

.644

.541

.733

3821

1846

41.3

47.7

42.1

2529

1518

4740

.345

.242

.625

2815

1848

39.6

42.8

36.3

2223

1218

4943

.044

.433

.628

2913

1850

44.3

46.4

37.0

3941

1918

5157

.260

.445

.043

4620

*C

onve

rted

tom

etric

tons

bym

ultip

lyin

gth

epe

sose

ries

by62

.193

(bec

ause

35lb

equa

ls16

.079

kg),

then

divi

ding

byth

eex

chan

gera

tes

inTa

ble

DA

.11.

**C

onve

rted

tom

etric

tons

bym

ultip

lyin

gth

epe

sose

ries

by36

.279

(bec

ause

60lb

equa

ls27

.564

kg),

then

divi

ding

byth

eex

chan

gera

tes

inTa

ble

DA

.11.

Sour

ces:

B.1

(35

lbpe

sada

,bes

tqua

lity)

,B.2

(35

lbpe

sada

,bes

tqua

lity

toN

orth

Am

eric

a),B

.3(3

5lb

pesa

da,b

estq

ualit

yto

Spai

n),a

ndB

.4(6

0lb

pesa

da,b

est

qual

ity):

and

Bro

ide,

‘Evo

luci

ón d

e lo

s pr

ecio

s’, p

p. 4

1-43

, 50,

Cua

dros

16-

18, 2

0.

M (u

nit v

alue

s): M

outo

ukia

s, ‘C

reci

mie

nto

en u

na e

cono

mía

’, p.

804

, Cua

dro

3.

P.1

(35

lb p

esad

a): A

non.

, ‘R

epor

t on

the

Trad

e’, p

. 42

P.2

(35

lb p

esad

a) a

nd P

.3 (6

0 lb

pes

ada)

: Ano

n., ‘

Prec

ios

corr

ient

es d

e pr

oduc

tos’

, p. 6

0.

- 287 -

Tabl

e D

A.14

Hid

e Pr

ices

in B

ueno

s Aire

s, 18

63-1

938

Type:

Dry

hid

es (o

$s p

er to

n)*

Sal

ted

hide

s (o

$s p

er to

n)*

Dry

hid

es (£

per

ton)

Sal

ted

hide

s (£

per

ton)

Source:

CH

G.1

CH

G.1

aD

GE

.1U

V.1

AC

HG

.2C

HG

.2a

DG

E.2

UV.

2C

HG

.1C

HG

.1a

DG

E.1

UV.

1A

CH

G.2

CH

G.2

aD

GE

.2U

V.2

1864

556

346

149

121

153

115

7131

2532

1865

495

308

128

103

131

101

6326

2127

1866

518

322

134

109

139

108

6728

2329

1867

559

348

148

117

149

113

7030

2430

1868

589

366

168

136

172

121

7534

2835

1869

554

345

163

132

168

116

7234

2835

1870

593

369

171

139

176

124

7736

2937

1871

620

386

200

163

207

131

8142

3444

1872

738

459

230

186

236

157

9849

4050

1873

784

488

253

200

254

162

101

5241

5218

7471

844

725

319

124

215

093

5340

5118

7567

041

724

618

323

314

087

5138

4918

7660

737

820

914

518

412

880

4430

3918

7768

442

522

717

121

714

489

4836

4618

7863

139

219

515

019

113

282

4131

4018

7966

341

220

916

020

313

886

4433

4218

8074

521

618

015

745

3818

8159

221

319

312

445

4118

8257

520

419

312

243

4118

8357

221

316

612

045

3518

8465

720

616

312

940

3218

8561

721

227

911

640

5318

8641

517

519

882

3539

1887

388

173

194

7734

3818

8824

316

714

248

3328

1889

217

136

127

4327

2518

9019

713

112

540

2625

1891

172

126

126

3525

25

- 288 -

Tabl

e D

A.14

(con

t.)Type:

Dry

hid

es (o

$s p

er to

n)*

Sal

ted

hide

s (o

$s p

er to

n)*

Dry

hid

es (£

per

ton)

Sal

ted

hide

s (£

per

ton)

Source:

CH

G.1

CH

G.1

aD

GE

.1U

V.1

AC

HG

.2C

HG

.2a

DG

E.2

UV.

2C

HG

.1C

HG

.1a

DG

E.1

UV.

1A

CH

G.2

CH

G.2

aD

GE

.2U

V.2

1892

189

189

127

117

117

3838

2523

2318

9319

519

713

012

512

539

3926

2525

1894

175

175

133

133

133

3535

2727

2718

9531

631

619

017

719

463

6338

3539

1896

285

285

166

173

173

5757

3334

3418

9729

829

817

215

315

359

5934

3030

1898

290

290

190

188

188

5858

3837

3718

9932

932

919

719

019

066

6640

3838

1900

332

332

204

199

199

6666

4140

4019

0133

033

018

919

019

066

6638

3838

1902

330

330

183

180

180

6666

3736

3619

0333

733

719

518

518

568

6839

3737

1904

358

358

186

185

185

7272

3737

3719

0540

440

422

722

422

481

8146

4545

1906

459

459

256

257

257

9292

5152

5219

0740

939

424

524

324

882

7949

4950

1908

288

288

202

206

206

5858

4041

4119

0938

340

627

526

827

077

8155

5454

1910

462

461

295

281

278

9292

5956

5619

1144

744

928

327

227

089

9057

5454

1912

544

549

328

318

316

109

110

6664

6319

1364

965

940

137

437

313

013

280

7575

1914

608

612

415

363

362

122

123

8473

7319

1559

159

842

042

842

811

912

084

8686

1916

753

480

493

154

9810

119

1777

065

653

216

013

711

119

1869

464

044

914

713

695

1919

843

841

672

188

187

150

1920

667

710

586

163

173

143

1921

397

533

356

7510

167

- 289 -

Tabl

e D

A.14

(con

t.)Type:

Dry

hid

es (o

$s p

er to

n)*

Sal

ted

hide

s (o

$s p

er to

n)*

Dry

hid

es (£

per

ton)

Sal

ted

hide

s (£

per

ton)

Source:

CH

G.1

CH

G.1

aD

GE

.1U

V.1

AC

HG

.2C

HG

.2a

DG

E.2

UV.

2C

HG

.1C

HG

.1a

DG

E.1

UV.

1A

CH

G.2

CH

G.2

aD

GE

.2U

V.2

1922

381

572

369

7010

668

1923

461

544

383

7993

6519

2448

551

836

786

9265

1925

548

448

388

104

8573

1926

517

388

339

9873

6419

2761

244

542

712

188

8419

2874

646

314

791

1929

472

305

9260

1930

345

268

5946

1931

290

253

4337

1932

244

201

4033

1933

267

213

4536

1934

296

225

4333

1935

316

248

4636

1936

343

281

5141

1937

487

381

7357

1938

335

268

4939

* D

urin

g 19

17-3

8 th

e go

ld p

eso

(o$s

) is a

not

iona

l mon

ey o

f acc

ount

, equ

ival

ent t

o 2.

27 p

aper

pes

os (m

$n).

Sour

ces:

A (A

rgen

tine

mea

tpac

kers

, ste

ers)

: Álv

arez

, Tem

as d

e hi

stor

ia e

conó

mic

a, p

p. 2

12-1

4.

CH

G: C

orté

s Con

de, H

alpe

rín D

ongh

i, an

d G

oros

tegu

i de

Torr

es, ‘

Evol

ució

n de

l com

erci

o ex

terio

r’, p

. 78.

DG

E: D

GEN

, Ext

ract

o es

tadí

stic

o, p

p. 2

04-0

5.

UV

(uni

t val

ues,

base

d on

who

lesa

le p

rices

): To

rnqu

ist,

Econ

omic

Dev

elop

men

t, pp

. 168

, 171

; and

Váz

quez

-Pre

sedo

, Est

adís

ticas

his

tóri

cas,

II, p

p. 2

06-0

7.

Exch

ange

rate

s: T

able

DA

.11.

- 290 -

Tabl

e D

A.15

Arg

entin

a’s E

xpor

t Pric

es, 1

780-

1938

Hid

es,

drie

dH

ides

,sa

lted

Jerk

edbe

efW

ool

Fat a

ndta

llow

Cat

tle*

She

epsk

ins

Whe

atM

aize

Whe

atflo

urLi

nsee

dG

oat s

kins

Px

inde

x**

1780

1516

1781

1515

1782

1516

1783

1818

1784

2021

1785

1515

1786

1414

1787

1819

1788

1819

1789

1718

1790

99

1791

1616

1792

1415

1793

1414

1794

1616

1795

2425

1796

2425

1797

1798

1799

1800

1801

1802

1803

1804

1805

1806

1807

- 291 -

Tabl

e D

A.15

(con

t.)H

ides

,dr

ied

Hid

es,

salte

dJe

rked

beef

Woo

lFa

t and

tallo

wC

attle

*S

heep

skin

sW

heat

Mai

zeW

heat

flour

Lins

eed

Goa

t ski

nsP

x in

dex*

*

1808

1809

1810

2324

1811

2324

1812

4244

1813

4647

1814

4243

1815

4244

1816

5556

1817

5658

1818

5860

1819

5759

1820

5456

1821

7138

7418

2277

4180

1823

7439

7618

2418

2518

2618

2718

2818

2957

2510

.358

1830

6328

8.0

6118

3157

237.

255

1832

5823

9.7

5718

3358

248.

827

3257

1834

6225

9.7

3228

6118

3557

249.

826

2857

1836

5623

12.1

2730

5818

3753

239.

025

2853

- 292 -

Tabl

e D

A.15

(con

t.)H

ides

,dr

ied

Hid

es,

salte

dJe

rked

beef

Woo

lFa

t and

tallo

wC

attle

*S

heep

skin

sW

heat

Mai

zeW

heat

flour

Lins

eed

Goa

t ski

nsP

x in

dex*

*

1838

4720

7.7

1925

4718

3936

176.

016

2136

1840

156.

114

1918

4143

228.

320

3045

1842

4323

5.4

2333

4418

4343

2410

.424

2246

1844

4325

7.9

3316

4518

4533

217.

428

1335

1846

2515

7.7

1814

2818

4725

158.

017

2029

1848

2212

8.0

1918

2618

4928

138.

827

2032

1850

3919

12.4

4223

4418

5143

208.

840

2546

1852

1853

1854

1855

1856

1857

1858

1859

1860

1861

1862

1863

1864

7131

1152

311.

656

7118

6563

269

5732

1.3

4865

1866

6728

954

351.

557

6918

6770

309

4533

1.4

5464

- 293 -

Tabl

e D

A.15

(con

t.)H

ides

,dr

ied

Hid

es,

salte

dJe

rked

beef

Woo

lFa

t and

tallo

wC

attle

*S

heep

skin

sW

heat

Mai

zeW

heat

flour

Lins

eed

Goa

t ski

nsP

x in

dex*

*

1868

7534

940

331.

555

6218

6972

349

3736

1.4

5659

1870

7736

1343

351.

557

6618

7181

4218

5035

1.8

7075

1872

9849

1368

361.

762

9018

7310

152

1356

341.

860

8318

7493

5317

6233

1.9

5885

1875

8751

2463

342.

157

8618

7680

4424

4934

2.0

4572

1877

8948

3056

342.

445

8118

7882

4125

5532

2.2

468.

877

1879

8644

2966

322.

440

6.8

3.7

8518

8080

4531

5631

3.2

6115

.85.

025

.181

1881

7545

3258

313.

048

13.5

3.8

21.0

7818

8270

4332

6332

3.2

3511

.44.

319

.179

1883

6545

2560

352.

543

7.7

5.0

15.4

7518

8460

4020

5629

2.2

307.

64.

015

.567

1885

5640

1845

281.

727

5.4

2.8

11.5

5518

8652

3518

5921

1.8

178.

63.

312

.561

1887

4934

2356

221.

731

6.5

3.1

10.9

7.5

6118

8846

3311

4516

1.7

296.

54.

712

.97.

154

1889

4227

1641

161.

734

7.0

5.6

16.4

7.1

5318

9040

2618

4420

1.5

366.

12.

313

.47.

351

1891

3525

1841

201.

432

8.3

4.8

13.3

8.9

5118

9238

2517

3320

3.1

326.

23.

910

.912

.449

1893

3926

2137

233.

132

4.6

3.7

7.0

7.8

104

5018

9435

2721

3420

4.8

273.

43.

85.

06.

561

4618

9563

3816

3317

5.0

243.

92.

66.

95.

994

4918

9657

3313

4015

5.0

264.

82.

07.

55.

995

5118

9759

3413

3717

4.9

216.

72.

911

.66.

110

157

- 294 -

Tabl

e D

A.15

(con

t.)H

ides

,dr

ied

Hid

es,

salte

dJe

rked

beef

Woo

lFa

t and

tallo

wC

attle

*S

heep

skin

sW

heat

Mai

zeW

heat

flour

Lins

eed

Goa

t ski

nsP

x in

dex*

*

1898

5838

1951

175.

128

6.9

2.6

9.9

6.8

117

6318

9966

4021

5819

5.7

424.

52.

36.

46.

875

6119

0066

4124

5123

7.6

425.

03.

46.

79.

712

770

1901

6638

2439

239.

434

5.8

3.4

7.6

9.7

139

6819

0266

3724

4826

8.0

405.

83.

98.

210

.414

372

1903

6839

2452

258.

748

4.9

3.2

8.7

7.2

130

6919

0472

3727

5722

6.8

465.

83.

68.

96.

410

271

1905

8146

3068

227.

062

6.0

4.2

7.5

8.0

113

8119

0692

5126

7926

7.7

705.

94.

07.

09.

511

087

1907

8249

2277

318.

470

6.2

4.7

7.4

9.4

124

8919

0858

4023

5428

8.7

437.

14.

99.

19.

381

8119

0977

5523

6828

9.4

518.

45.

29.

79.

893

9319

1092

5922

7833

10.4

547.

74.

58.

614

.811

810

019

1189

5727

7731

10.5

527.

14.

48.

016

.210

298

1912

109

6632

7130

10.7

547.

54.

510

.513

.310

798

1913

130

8034

7632

12.7

597.

34.

711

.69.

811

710

019

1412

373

8130

627.

64.

413

.410

.210

419

1512

086

9531

6810

.64.

317

.49.

411

719

1616

010

511

641

898.

95.

213

.711

.912

819

1716

011

116

662

127

13.5

9.3

23.6

18.4

175

1918

147

9520

759

130

11.9

5.2

17.6

18.7

161

1919

188

150

206

7112

013

.76.

618

.326

.019

519

2016

314

317

770

117

16.7

8.2

22.0

21.8

195

1921

7567

5835

3514

.39.

623

.616

.014

319

2270

6845

3337

9.6

6.6

21.0

17.3

109

1923

7965

7639

538.

36.

813

.617

.911

719

2486

6510

939

908.

56.

713

.417

.912

519

2510

473

126

4310

212

.17.

015

.719

.314

719

2698

6496

3581

10.9

4.9

15.1

13.9

119

1927

121

8410

129

819.

45.

113

.713

.311

8

- 295 -

Tabl

e D

A.15

(con

t.)H

ides

,dr

ied

Hid

es,

salte

dJe

rked

beef

Woo

lFa

t and

tallo

wC

attle

*S

heep

skin

sW

heat

Mai

zeW

heat

flour

Lins

eed

Goa

t ski

nsP

x in

dex*

*

1928

147

9112

633

929.

37.

012

.214

.913

819

2992

6010

433

738.

26.

611

.318

.113

319

3059

4655

2546

7.1

4.5

11.4

14.2

9819

3143

3738

1636

3.7

3.0

8.2

8.8

7019

3240

3340

1727

4.8

2.9

7.6

6.9

6419

3345

3642

1639

4.1

2.9

6.2

8.0

6219

3443

3370

1650

4.0

4.1

6.9

10.3

7419

3546

3652

2244

4.6

2.9

7.6

10.1

7619

3651

4169

2363

6.1

3.4

9.4

12.3

9019

3773

5792

2174

8.0

4.3

11.2

13.3

108

1938

4939

6118

446.

14.

57.

912

.395

* £

per h

ead.

** 1

910

= 10

0. In

clud

es th

e pr

ices

in T

able

DA

.16.

See

App

endi

x 4.

1.

Not

e: A

ll se

ries a

re in

£ p

er m

etric

ton,

exc

ept c

attle

.

Sour

ces:

Exch

ange

rate

s: T

able

DA

.11.

Hid

e pr

ices

: Tab

les D

A.1

3 an

d D

A.1

4.

Oth

erex

port

pric

ess:

Com

pile

dfr

omB

roid

e,‘E

volu

ción

delo

spr

ecio

s’,

pp.

26,

30,

34,

Cua

dros

9,11

,an

d13

;C

orté

sC

onde

,H

alpe

rinD

ongh

i,an

dG

oros

tegu

ide

Torr

es,‘

Evol

ució

nde

lco

mer

cio’

,pp.

72-7

9;To

rnqu

ist,

Econ

omic

Dev

elop

men

t,pp

.167

-72;

Bun

ge,I

nter

cam

bio

econ

ómic

o,ch

.11;

and

Váz

quez

-Pre

sedo

, Est

adís

ticas

his

tóri

cas,

II, p

p. 1

94-2

21.

- 296 -

Tabl

e D

A.16

Arg

entin

a’s

Expo

rt Pr

ices

, 191

0-19

38Barley

Beef, chilled

Beef, conserved

Beef, frozen

Bran

Butter

Oats

Sugar

Quebracho logs

Quebracho extract

Rye

Cotton

Sheep skins, bare

Mutton, frozen and chilled

Casein

Guts, salted

Offal, frozen

Wool, washed

Wool, clean

Px index*

1910

5.6

2835

283.6

126

4.4

363.3

172.5

100

1911

4.4

2848

284.3

133

4.6

363.2

152.5

981912

4.8

2940

293.7

132

4.9

382.6

134.8

981913

4.9

3635

363.5

121

4.6

352.6

135.2

100

1914

4.9

4157

413.7

130

5.0

352.6

135.6

4940

104

1915

5.3

4371

432.2

134

6.4

352.6

326.6

4840

117

1916

5.2

4684

463.2

154

4.4

462.9

416.7

69106

3940

1013

101

128

1917

8.8

4673

403.8

159

7.8

523.0

3120.9

69137

3957

1344

424

175

1918

5.6

4897

582.9

169

6.3

643.3

218.5

101

7649

3827

41300

161

1919

6.8

69113

733.5

169

6.2

434.1

347.8

5370

6030

1942

228

195

1920

8.4

5277

525.7

169

7.4

484.9

3313.1

7681

5230

2840

187

139

195

1921

9.3

4957

505.3

169

7.4

444.8

2213.0

3942

4827

2936

149

73143

1922

7.2

2655

265.1

137

7.1

303.9

218.3

4330

2326

3514

148

67109

1923

6.8

3542

294.5

168

6.7

633.7

187.1

5033

3734

3627

306

94117

1924

7.6

3452

305.3

152

6.6

373.9

167.4

7954

4727

4426

213

152

125

1925

10.4

4052

346.1

162

8.2

264.4

1813.1

7187

4937

5826

277

161

147

1926

6.6

3551

324.1

139

6.1

303.9

177.7

6285

3238

4428

175

119

119

1927

7.7

3150

285.0

139

6.4

134.2

218.6

5776

3339

5526

214

111

118

1928

9.3

4151

366.1

149

9.0

324.8

229.8

6378

4236

5038

226

124

138

1929

8.2

4858

426.0

166

7.9

355.9

229.3

7481

4354

5633

245

131

133

1930

3.4

3950

343.1

109

3.3

274.3

183.4

5965

3442

4628

188

9198

1931

3.5

3545

313.1

106

3.3

323.9

153.6

8645

3111

4625

150

7370

1932

4.8

2518

233.3

803.8

283.0

104.8

3734

257

4222

8165

641933

3.3

2619

192.6

683.1

303.3

113.2

4217

2426

4822

7846

621934

4.0

3022

203.9

703.8

323.6

134.4

6315

3336

4923

108

5274

- 297 -

Tabl

e D

A.16

(con

t.)

Barley

Beef, chilled

Beef, conserved

Beef, frozen

Bran

Butter

Oats

Sugar

Quebracho logs

Quebracho extract

Rye

Cotton

Sheep skins, bare

Mutton, frozen and chilled

Casein

Guts, salted

Offal, frozen

Wool, washed

Wool, clean

Px index*

1935

4.7

3825

204.0

904.5

333.8

184.1

6316

5335

5622

101

6276

1936

5.2

4126

214.5

944.9

334.1

175.1

6933

5948

5820

135

6590

1937

7.2

4239

273.5

925.3

313.9

1810.4

5843

6152

4531

189

115

108

1938

7.5

4252

284.8

105

5.1

354.1

185.9

4729

6123

3234

139

8495

* 19

10 =

100

. Inc

lude

s th

e pr

ices

from

Tab

le D

A.1

5. S

ee A

ppen

dix

4.1.

Not

e: A

ll se

ries

are

in £

per

met

ric to

n.

Sour

ces:

Exch

ange

rate

s: T

able

DA

.11.

Pric

es:C

ompi

led

from

Bun

ge,I

nter

cam

bio

econ

ómic

o,ch

.11;

Torn

quis

t,Ec

onom

icD

evel

opm

ent,

pp.1

67-7

2;an

dV

ázqu

ez-P

rese

do,E

stad

ístic

ashi

stór

icas

,II

, pp.

194

-221

.

- 298 -

Table DA.17Argentina’s Proxy Import Price Index, 1780-1938

Px indices, 1913=100* ProxyPi Index**Britain USA France Brazil Italy Germany

1780 395 3201781 389 3161782 400 3241783 393 3191784 386 3131785 388 3151786 392 3181787 394 3201788 388 3151789 390 3161790 393 73 3191791 401 63 3151792 415 61 3221793 423 72 3371794 424 73 3391795 429 113 3711796 456 134 4021797 439 131 3891798 433 157 3971799 461 177 4271800 469 107 3951801 474 117 4051802 466 98 3861803 463 97 3841804 459 108 3881805 465 120 4001806 443 107 3761807 411 102 3521808 395 83 3281809 370 85 223 3121810 373 100 235 3241811 319 112 233 2941812 356 117 225 3201813 362*** 112 221 3211814 368 100 189 3141815 326 124 189 2981816 305 158 162 2911817 284 174 195 2851818 293 182 206 2961819 279 144 184 2711820 251 106 160 2351821 235 88 157 149 2171822 219 91 154 119 2021823 212 79 146 135 1961824 206 86 140 103 1871825 216 105 148 128 2051826 202 78 137 108 1841827 187 69 126 96 1681828 183 69 124 90 1641829 167 73 122 79 154

- 299 -

Table DA.17 (cont.)Px indices, 1913=100* Proxy

Pi Index**Britain USA France Brazil Italy Germany1830 164 70 116 71 1481831 160 68 112 53 1391832 157 72 111 68 1431833 149 80 115 70 1421834 148 91 123 70 1451835 158 103 124 61 1511836 164 107 134 68 1591837 152 93 123 63 1461838 145 79 121 48 1341839 143 104 119 54 1401840 131 66 119 61 1281841 131 73 117 58 1281842 124 65 113 52 1191843 116 53 115 45 1101844 117 61 124 41 1131845 124 53 125 40 1151846 114 64 128 45 1151847 122 78 110 41 1171848 104 64 112 43 1061849 101 58 121 37 1021850 105 82 127 49 1141851 102 84 128 51 1131852 104 65 138 53 1151853 121 64 155 50 1271854 121 80 154 61 1321855 111 81 147 57 1241856 117 84 156 64 1321857 125 97 153 70 1391858 112 88 144 70 1281859 115 86 151 63 1301860 113 82 148 78 1301861 113 83 139 75 1271862 135 73 141 76 127 1371863 149 48 141 85 123 1391864 157 35 140 96 121 1391865 139 47 137 83 123 1331866 144 61 130 79 115 1351867 135 73 123 72 119 1301868 126 69 119 71 117 1241869 125 74 117 58 122 1211870 122 87 115 66 122 1231871 122 90 115 65 123 1231872 135 89 117 64 144 1311873 140 85 113 94 137 1351874 132 88 108 102 128 1301875 124 90 106 91 121 1241876 114 84 105 98 140 1201877 110 86 103 89 124 1161878 106 87 98 81 113 1111879 99 93 99 73 116 1071880 103 102 101 96 112 130 1131881 99 105 100 79 114 131 109

- 300 -


Pi Index**Britain USA France Brazil Italy Germany1882 101 107 99 63 111 134 1091883 97 102 97 48 109 130 1041884 94 98 93 57 104 120 1011885 90 91 90 53 101 110 961886 86 86 88 48 99 106 921887 86 86 87 68 93 107 941888 86 90 88 86 87 109 951889 87 86 91 87 93 111 971890 91 85 91 86 95 111 971891 90 88 90 82 88 107 961892 86 82 87 81 87 101 911893 86 80 88 101 82 100 911894 82 70 82 92 74 93 851895 79 72 80 85 81 93 841896 79 71 79 74 75 95 831897 78 69 80 55 75 95 821898 79 69 81 52 74 95 821899 82 72 86 53 78 99 861900 95 81 87 69 79 102 941901 90 79 85 59 79 98 901902 86 81 85 53 82 95 891903 86 87 86 56 86 96 901904 87 87 85 71 84 97 911905 87 84 87 76 86 98 921906 92 90 91 73 91 97 961907 96 95 92 73 96 102 1001908 93 90 91 71 89 97 961909 89 94 93 82 90 96 951910 93 102 97 110 96 96 1001911 95 94 99 115 99 97 971912 96 96 99 129 99 99 981913 100 100 100 100 100 100 1001914 102 96 103 82 102 99† 991915 129 108 148 74 105 124† 1181916 168 138 146 87 136 144† 1461917 225 181 209 87 186 193† 1941918 253 211 293 90 239 233† 2301919 277 237 302 148 267 248† 2561920 358 309 225 108 225 264† 2811921 269 199 169 58 163 186† 1971922 201 158 169 71 157 154† 1651923 190 164 146 70 140 144† 1571924 189 167 155 98 143 145† 1611925 184 154 134 118 139 142 1551926 174 141 119 112 146 137 1461927 165 132 119 94 154 140 1421928 165 135 118 108 143 142 1431929 161 134 113 99 134 139 1381930 154 120 107 62 118 132 1251931 138 98 92 42 109 124 1091932 129 110 95 46 116 144 1151933 128 95 91 36 110 142 107

- 301 -


Pi Index**Britain USA France Brazil Italy Germany1934 129 94 92 33 106 142 1051935 129 99 92 27 112 140 1061936 132 99 97 31 114 140 1091937 143 106 108 35 113 154 1171938 146 99 94 23 114 163 112

* When not given in sterling, the series were converted using the exchange rates in TableDA.6.

** See Appendix 4.1, pages 187-88.

*** Interpolated.

† Interpolated, following the geometric mean of the export indices of Britain, France, and theUnited States.

Sources:

Brazil: Calculated from IBGE, Estatísticas Históricas, pp. 345-56. See Appendix 4.1, page188.

Britain: Cuenca Esteban, ‘Rising Share’, p. 901, App. Table 1; Imlah, Economic Elements, pp.94-98, Table 8; and Feinstein, National Income, pp. T132-32, Table 61.

France: Kindleberger, ‘Industrial Europe’s’, p. 21; and Lévy-Leboyer, ‘Héritage de Simiand’,pp. 108-111, Table 5

Germany: Hoffmann, Wachstum der deutschen, pp. 606-09, Table 151.

Italy: Federico et al, Commercio estero, pp. 228-29, Tabella 7b.

United States: Irwin, ‘Exports and Imports’.

- 302 -

Tabl

e D

A.18

The

100

Larg

est C

orpo

ratio

ns R

egis

tere

d in

Arg

entin

a, 1

914

Ran

kC

orpo

ratio

nA

ctiv

ityN

atio

nalit

y*C

apita

l**1

Ferr

ocar

ril C

entra

l Arg

entin

oR

ailw

ays

Fore

ign

(Brit

ish)

58

0.1

2Fe

rroc

arril

de

Bue

nos

Aire

s al

Pac

ífico

Rai

lway

sFo

reig

n (B

ritis

h)

333.

83

Ferr

ocar

ril C

entra

l de

Cór

doba

Rai

lway

sFo

reig

n (B

ritis

h)

230.

94

Ang

lo A

rgen

tine

Tram

way

sP

asse

nger

tran

spor

tM

ixed

(Ang

lo-A

rgen

tine)

20

0.0

5B

anco

Hip

otec

ario

Fra

nco

Arg

entin

oM

ortg

ages

Mix

ed (A

rgen

tine,

Bel

gian

, Ger

man

) 14

5.0

6B

anco

Esp

añol

del

Río

de

la P

lata

Ban

king

Mix

ed (A

rgen

tine,

Brit

ish,

Fre

nch,

Spa

nish

) 13

7.5

7B

anco

de

la N

ació

n A

rgen

tina

Ban

king

Arg

entin

e (g

over

nmen

t) 12

8.0

8B

anco

El H

ogar

Arg

entin

oM

utua

l cre

dit

Arg

entin

e 98

.09

Ferr

ocar

ril d

e E

ntre

Río

sR

ailw

ays

Fore

ign

(Ang

lo-F

renc

h)

91.0

10Fe

rroc

arril

de

Ros

ario

a P

uerto

Bel

gran

oR

ailw

ays

Mix

ed (A

rgen

tine,

Bel

gian

, Fre

nch)

78

.411

Ban

co d

e la

Pro

vinc

ia d

e B

ueno

s A

ires

Ban

king

Arg

entin

e (g

over

nmen

t) 75

.012

Ban

co F

ranc

és d

el R

ío d

e la

Pla

taB

anki

ngM

ixed

(Fra

nco-

Arg

entin

e)

70.0

13N

orth

Brit

ish

Mer

cant

ile In

sura

nce

Com

pany

Insu

ranc

eFo

reig

n (B

ritis

h)

50.0

14C

ompa

ñía

Prim

itiva

de

Gas

de

Bue

nos

Aire

sG

as fa

ctor

yFo

reig

n (B

ritis

h)

43.5

15R

oyal

Insu

ranc

e C

ompa

nyLi

fe in

sura

nce

Fore

ign

(Brit

ish)

42

.516

Arg

entin

e N

aveg

atio

n C

ompa

ny (N

icol

ás M

ihan

ovic

h)S

hipp

ing

Mix

ed (A

nglo

-Arg

entin

e)

35.3

17A

ustra

lian

Mer

cant

ile L

and

and

Fina

nce

Agr

icul

ture

, fin

ance

Mix

ed (A

rgen

tine,

Aus

tralia

n, B

ritis

h)

34.4

18S

cotti

sh U

nión

y N

acio

nal

Fire

insu

ranc

eFo

reig

n (B

ritis

h)

34.4

19Fe

rroc

arril

Mid

land

de

Bue

nos

Aire

sR

ailw

ays

Fore

ign

(Brit

ish)

34

.220

Ban

co G

alic

ia y

Bue

nos

Aire

sB

anki

ngA

rgen

tine

34.0

21S

outh

Am

eric

an S

tore

s G

ath

y C

have

s Lt

da

Ret

ailin

gM

ixed

(Ang

lo-A

rgen

tine)

33

.422

M.S

. Bag

ley

y C

íaB

iscu

itsA

rgen

tine

33.0

23Lo

ndon

and

Lan

cash

ire F

ire In

sura

nce

Com

pany

Fire

insu

ranc

eFo

reig

n (B

ritis

h)

30.0

24B

anco

Lon

dres

y R

ío d

e la

Pla

taB

anki

ngFo

reig

n (B

ritis

h)

28.0

25B

anco

Ang

lo S

ud A

mer

ican

oB

anki

ngFo

reig

n (B

ritis

h)

27.5

The

Riv

er P

late

Tru

st L

oan

Age

ncy

Mor

tgag

esM

ixed

(Ang

lo-A

rgen

tine)

27

.526

Lacr

oze

de B

ueno

s A

ires

Pas

seng

er tr

ansp

ort

Mix

ed (A

nglo

-Arg

entin

e)

25.0

27U

nite

d R

iver

Pla

te T

elep

hone

Com

pany

Tele

phon

esFo

reig

n (B

ritis

h)

24.0

- 303 -

Tabl

e D

A.18

(con

t )R

ank

Cor

pora

tion

Act

ivity

Nat

iona

lity*

Cap

ital**

28G

uard

ian

Ass

uran

ceFi

re in

sura

nce

Fore

ign

(Brit

ish)

22

.929

Ban

co It

alia

y R

ío d

e la

Pla

taB

anki

ngM

ixed

(Arg

entin

e, It

alia

n, S

wis

s)

22.7

30S

ocie

dad

Hip

otec

aria

Bel

ga A

mer

ican

aM

ortg

ages

Mix

ed (B

elgo

-Arg

entin

e)

22.0

30C

ompa

ñía

de E

lect

ricid

ad d

e B

ueno

s A

ires

Ele

ctric

ityM

ixed

(Fra

nco-

Arg

entin

e an

d ot

hers

) 22

.031

Ferr

ocar

ril C

entra

l de

Bue

nos

Aire

sR

ailw

ays

Arg

entin

e 20

.232

Cen

tral a

nd S

outh

Am

eric

an T

eleg

raph

Com

pany

Te

legr

aphs

Fore

ign

(US

) 20

.033

Lieb

ig's

Ext

ract

of M

eat C

ompa

nyB

eef

Fore

ign

(Bel

gian

, Brit

ish,

Ger

man

)18

.334

Cré

dito

Ter

ritor

ial S

ud A

mer

ican

oM

ortg

ages

Mix

ed (A

rgen

tine,

Bel

gian

, Fre

nch)

18

.0S

ocie

dad

Gen

eral

Bel

ga A

rgen

tina

Mor

tgag

esM

ixed

(Bel

go-A

rgen

tine)

18

.0C

atal

inas

War

ehou

ses

and

Mol

e C

ompa

nyW

areh

ousi

ngM

ixed

(Ang

lo-A

rgen

tine)

18

.035

Har

rods

Ret

ailin

gM

ixed

(Ang

lo-A

rgen

tine)

17

.336

Ern

esto

Tor

nqui

st C

ompa

nyB

anki

ngM

ixed

(Bel

go-A

rgen

tine)

17

.037

La P

lata

Col

d S

tora

geM

eatp

acki

ngM

ixed

(Arg

entin

e, B

ritis

h, U

S)

17.0

38C

omp

Arg

ent

de H

ierr

os y

Ace

ros

(P. V

asen

a e

hijo

s)M

etal

urgy

Mix

ed (A

nglo

-Arg

entin

e)

16.5

39Le

ach'

s A

rgen

tine

Est

.S

ugar

fact

ory

Fore

ign

(Brit

ish)

16

.040

New

Zea

land

Insu

ranc

e C

ompa

nyIn

sura

nce

Mix

ed (A

rgen

tine,

Aus

tralia

n, B

ritis

h, N

ew Z

eala

nder

) 15

.541

Ban

co F

ranc

és y

Ital

iano

Ban

king

Fore

ign

(Fra

nco-

Italia

n)

15.0

Ban

co A

lem

án T

rans

atlá

ntic

oB

anki

ngFo

reig

n (G

erm

an)

15.0

Cer

vece

ría A

rgen

tina

de Q

uilm

esB

rew

ing

Mix

ed (A

rgen

tine,

Bel

gian

, Brit

ish,

Fre

nch,

Ger

man

) 15

.042

Ban

co L

ondr

es y

Bra

sil

Ban

king

Fore

ign

(Brit

ish)

14

.343

Est

able

cim

ient

os A

rgen

tinos

de

Bov

rilC

onse

rved

mea

tsM

ixed

(Arg

entin

e, B

elgi

an, B

ritis

h)

14.1

44Th

e G

ener

al A

ccid

ent F

ire A

ssur

ance

Cor

por

Insu

ranc

eFo

reig

n (B

ritis

h)

13.2

45M

uelle

s y

Dep

ósito

s de

l Pue

rto d

e la

Pla

taP

ort

Arg

entin

e 13

.046

Com

pañí

a S

ansi

nena

de

Car

nes

Con

gela

das

Mea

tpac

king

Mix

ed (A

rgen

tine,

Bel

gian

, Brit

ish)

11

.647

Ban

co B

ritán

ico

de la

Am

éric

a de

l Sud

Ban

king

Fore

ign

(Brit

ish)

11

.5C

rédi

to T

errit

oria

l Arg

entin

oM

ortg

ages

Fore

ign

(Fre

nch)

11

.5

- 304 -

Tabl

e D

A.18

(con

t )R

ank

Cor

pora

tion

Act

ivity

Nat

iona

lity*

Cap

ital**

48A

llian

ce A

ssur

ance

Insu

ranc

eFo

reig

n (B

ritis

h)

11.5

Cor

y B

roth

ers

Com

pany

Coa

l im

porte

rsFo

reig

n (B

ritis

h)

11.5

49Le

desm

a S

ugar

Est

ates

and

Ref

inin

g C

ompa

nyS

ugar

fact

ory

Arg

entin

e 11

.050

Pop

ular

Arg

entin

oB

anki

ngA

rgen

tine

10.5

51C

rédi

to T

errit

oria

l de

San

ta F

eM

ortg

ages

Mix

ed (F

ranc

o-A

rgen

tine)

10

.452

Bod

egas

y V

inne

dos

Dom

ingo

Tom

baW

ines

, alc

ohol

sM

ixed

(Ang

lo-A

rgen

tine)

10

.353

Ban

co G

erm

ánic

o de

la A

mér

ica

del S

udB

anki

ngFo

reig

n (G

erm

an)

10.0

Soc

ieda

d H

ipot

ecar

ia H

olan

desa

del

Pla

taM

ortg

ages

Mix

ed (A

rgen

tine,

Dut

ch)

10.0

Cré

dito

Ter

ritor

ial d

el N

orte

Mor

tgag

esM

ixed

(Arg

entin

e, B

elgi

an, F

renc

h)

10.0

El S

alad

illo

Land

sal

esA

rgen

tine

10.0

Lond

on A

ssur

ance

Insu

ranc

eFo

reig

n (B

ritis

h)

10.0

Bod

egs

y Vi

ñedo

s G

iol

Vine

yard

s, w

ine

Arg

entin

e 10

.054

Mer

cado

Cen

tral d

e Fr

utos

Who

lesa

ling

Mix

ed (A

nglo

-Arg

entin

e)

9.7

55S

ocié

té d

e P

reis

Hyp

othé

caire

s en

Arg

entin

eM

ortg

ages

Mix

ed (A

rgen

tine,

Bel

gian

, Fre

nch)

9.

0La

s P

alm

as d

el C

haco

Aus

tral

Woo

d, s

ugar

Arg

entin

e 9.

056

Soc

ieda

d A

rgen

tina

de E

dific

ació

nR

eal e

stat

eM

ixed

(Fra

nco-

Arg

entin

e)

8.8

57S

anta

Ana

Sug

ar fa

ctor

yM

ixed

(Fra

nco-

Arg

entin

e)

8.2

58La

Coo

pera

tiva

Nac

iona

l de

Con

sum

osC

omm

erce

Fore

ign

(Brit

ish)

8.

059

Roy

al E

xcha

nge

Ass

uran

ceFi

re in

sura

nce

Fore

ign

(Brit

ish)

7.

960

Cer

vece

ría B

ierc

kert

Bee

rFo

reig

n (B

ritis

h)

7.8

61P

icca

rdo

y C

íaC

igar

ette

sA

rgen

tine

7.5

62S

ocie

dad

Terr

itoria

l Bel

ga-A

rgen

tina

Mor

tgag

esM

ixed

(Arg

entin

e, B

elgi

an, G

erm

an)

7.5

La H

olan

da A

rgen

tina

Mor

tgag

esFo

reig

n (D

utch

) 7.

5La

Agr

ícol

a G

anad

era

Auc

tion

hous

eA

rgen

tine

7.5

63N

uevo

Ban

co It

alia

noB

anki

ngM

ixed

(Ita

lo-A

rgen

tine)

7.

064

Hid

ro-e

léct

ric d

e Tu

cum

ánE

lect

ric p

ower

Mix

ed (A

nglo

-Arg

entin

e)

7.0

- 305 -

Tabl

e D

A.18

(con

t )R

ank

Cor

pora

tion

Act

ivity

Nat

iona

lity*

Cap

ital**

65A

zuca

rera

Con

cepc

ión

Sug

ar, a

lcoh

olA

rgen

tine

6.8

66La

Iber

o P

late

nse

Loan

sM

ixed

(Arg

entin

e, B

ritis

h, F

renc

h)

6.8

Des

tiler

ía, B

odeg

as y

Cer

vece

ría G

erm

ania

Dis

tillin

g, b

rew

ing

Arg

entin

e 6.

867

Dro

guer

ía d

e la

Est

rella

Pha

rmac

eutic

als

Fore

ign

(var

ious

) 6.

368

Com

pañí

a de

Agu

as C

orrie

ntes

de

Bue

nos

Aire

sP

otab

le w

ater

Mix

ed (A

nglo

-Arg

entin

e)

6.2

69In

dust

rial y

Pas

toril

Bel

ga S

ud A

mer

ican

aM

ortg

ages

Fore

ign

(Bel

gian

, Fre

nch)

6.

0C

orpo

raci

ón F

inan

cier

a e

Inm

obili

aria

Arg

entin

aR

eal e

stat

eM

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- 306 -

Table DA.19Land Ownership in Buenos Aires Province, 1836-90

(a) Individual distribution

Amount of land, %Holdings (has): 1836 1864 1890

101-500 0.1 1.9 7.7501-1000 0.6 4.9 12.8

1001-1750 1.9 10.0 16.01751-2500 2.6 10.5 11.12501-3750 8.1 12.3 11.73751-5000 9.9 9.4 8.8

5001-10000 24.1 24.5 14.710001-15000 18.3 11.4 6.815001-30000 20.3 11.7 6.3

30000+ 14.2 3.4 4.1Total (ha) 1,797,468 2,408,259 2,394,616

Number of holdings, %Holdings (has): 1836 1864 1890

101-500 3.3 15.3 39.5501-1000 5.2 18.8 23.9

1001-1750 9.7 20.8 16.81751-2500 8.2 13.8 7.32501-3750 16.7 11.0 5.33751-5000 15.2 6.2 2.8

5001-10000 23.0 9.8 3.010001-15000 10.4 2.5 0.815001-30000 5.9 1.5 0.4

30000+ 2.2 0.2 0.2Total (no.) 269 869 1,740

- 307 -

Table DA.20 (cont.)(b) Family distribution

Amount of land, %Holdings (has): 1836 1864 1890

101-500 0.1 1.8 5.1501-1000 0.6 4.0 8.0

1001-1750 1.7 7.2 9.51751-2500 2.5 8.2 8.32501-3750 7.7 10.1 11.23751-5000 9.6 6.3 7.5

5001-10000 21.3 20.7 13.810001-15000 15.6 12.6 9.315001-30000 23.0 20.5 18.0

30000+ 17.9 8.6 9.3Total (ha) 1,797,468 2,408,259 2,394,616

Number of holdings, %Holdings (has): 1836 1864 1890

101-500 3.5 17.5 38.5501-1000 5.5 17.9 21.3

1001-1750 9.1 18.4 13.81751-2500 8.3 13.1 7.72501-3750 16.9 11.0 7.23751-5000 15.7 5.1 4.2

5001-10000 21.7 9.9 3.710001-15000 9.4 3.2 1.515001-30000 7.1 3.2 1.6

30000+ 2.8 0.7 0.4Total (no.) 254 719 1,740

Note: The figures are for the aggregated holdings in all 16 counties. Holdings of 100 hectaresand less were not included.

Source: Sabato, ‘Wool Production’, pp. 333-42

- 308 -

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